online voting system research paper

Making Votes Count with Internet Voting

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• Published: 02 March 2020
• Volume 43 , pages 1511–1533, ( 2021 )

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• Micha Germann   ORCID: orcid.org/0000-0002-5217-3240 1  

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This paper reassesses the claim that electronic voting systems help voters to avoid common mistakes that lead to their votes remaining uncounted. While prior studies have come to mixed conclusions, I provide new, more robust evidence based on a case study of extended Internet voting trials in Geneva canton, Switzerland. The trials almost exclusively involved referendum votes. For causal identification I exploit the unique circumstance that federal safety legislation created a near-natural experiment, with some of the canton’s municipalities participating in the trials and others not. Using difference-in-differences estimation, I find that the residual vote rate decreased by an average of 0.3 percentage points if municipalities offered the possibility to vote online in addition to (mostly optically scanned) paper ballots. For cantonal measures, which are located towards the bottom of ballot papers in Geneva, the reduction increases to 0.5 percentage points. These remain relatively modest effects, and I find no evidence for a knock-on effect on electoral outcomes. However, on average only around 20% of votes were cast online where the opportunity existed, and online voting was most popular among voters with high levels of education. Despite the small effect sizes, the results of this study therefore point to the potential of Internet and, more generally, electronic voting technology to reduce avoidable voter mistakes.

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Introduction

Electoral turnout, and how to improve it, range among the core concerns in political science. However, more frequently overlooked is the fact that even if citizens participate in elections, their votes do not always enter the final count. Comparative evidence suggests that between 3 and 5% of votes cast remain uncounted (i.e., are ruled blank or invalid) in the average democratic election (Martinez i Coma and Werner 2019 ; Uggla 2008 ). In some contexts, such as Latin America, it is not uncommon for the number of uncounted votes to exceed 10% of votes cast (Power and Garand 2007 ).

Uncounted votes (henceforth also referred to as residual votes) can reflect the actual will of voters. Some voters choose to intentionally spoil their ballots as a form of protest. Others choose to skip some of the less salient races on a ballot (Solvak and Vassil 2015 ). However, residual votes often also result from mistakes on the side of voters. For example, uncertainty about electoral rules can lead voters to vote for more candidates than are allowed under the rules, leading to the invalidation of their votes (Carman et al. 2008 ). Moreover, voters may accidentally skip races due to oversight, or they may fail to mark ballots in a sufficiently clear way. This paper considers the potential of Internet voting technology to reduce such accidental residual votes.

Accidental residual votes range among the lesser known challenges to democratic legitimacy and the quality of representation. Of course, intentional residual votes are problematic as well because they often reflect voter alienation. However, citizens who accidentally cast residual votes would have wanted to make their voices heard, but failed to do so. Therefore, accidental residual votes contravene a central democratic principle: that the votes of citizens must be accurately interpreted and counted (Dahl 1989 , ch. 8). What is more, accidental residual votes are unlikely to be randomly distributed across different populations of voters. Existing evidence suggests that voters with low educational attainment are more prone to errors that lead to their votes not being counted (Bullock and Hood 2002 ; Fujiwara 2015 ; Sinclair and Alvarez 2004 ). Where education levels are correlated with race and ethnicity, such as in the U.S., that can mean that voter errors are disproportionately committed by members of ethnic minorities (Tomz and Van Houweling 2003 ). By implication, accidental residual votes are likely to reinforce well-known inequalities in representation stemming from unequal participation. In closely fought contests, they may even affect electoral outcomes.

Various proposals have been made for how to reduce accidental residual votes, including better training of polling staff, improved ballot design, and voter education campaigns (Herrnson et al. 2012 ; Herron and Sekhon 2003 ; Kimball and Kropf 2005 ; Niemi and Herrnson 2003 ). Another prominent proposal concerns error-preventing voting technologies, such as electronic voting systems (Alvarez and Hall 2008 ). Paper ballots remain the most common voting method in contemporary democracies, more than 400 years after their invention (Reynolds and Steenbergen 2006 ). But when equipped with a pen and piece of paper, there is often little standing in the way of voters making avoidable errors. While they have grown controversial in recent years due to vulnerability to fraud, an advantage of electronic voting systems is that they can be programmed to prevent voters from making such mistakes. As a result, electronic voting should make it more likely that votes enter the final count and, thus, increase effective participation.

However, empirical studies of whether electronic voting technology lives up to this promise have come to mixed conclusions (e.g., Ansolabehere and Stewart 2005 ; Stewart 2006 ). This paper provides new, more robust evidence on the effect of electronic voting technology on residual votes. While prior studies focused on electronic voting machines located in polling stations, this study extends the focus to Internet voting, a novel form of electronic voting that is increasingly discussed and experimented with around the globe (Alvarez et al. 2009 ). Specifically, I study the case of Geneva canton, Switzerland, where Internet voting (henceforth also referred to as i-voting or online voting) has been trialed on an extended basis from 2003 to 2005 and from 2008 onward. A limitation of the Geneva case is that experimentation with i-voting has largely involved referendums while eschewing elections. However, within these constraints, Geneva canton holds valuable lessons because it enables the estimation of Internet voting’s effect on uncounted ballots with comparatively high internal validity. The i-voting roll-out in Geneva canton resembles a natural experiment because, since the very first trials, federal safety legislation has been in place that led to between-municipality variation in the availability of i-voting, with i-voting being offered in some but not other municipalities. In turn, this permits to hold constant many sources of confounding that could have afflicted prior studies, including jurisdiction-specific electoral laws and counting practices as well as varying electoral dynamics.

Using difference-in-differences estimation, I find that the residual vote rate decreased by an average of 0.3 percentage points if municipalities offered the possibility to vote online in addition to (mostly optically scanned) paper ballots. Footnote 1 For cantonal (i.e., regional) measures, which in Geneva are located towards the bottom of ballot papers, the effect increases to a minus of 0.5 percentage points. These remain relatively modest effects, and additional analyses suggest that the reduction in uncounted ballots did not have a knock-on effect on electoral outcomes. However, only around 20% of votes tended to be cast online where the opportunity existed. Online voters also tend to have above-average education and, as a group, could thus be less prone to voting errors. Despite the relatively small effect sizes, the results of this study therefore point to the potential of Internet and, more generally, electronic voting technology to reduce avoidable voter mistakes.

The fiasco of the 2000 U.S. presidential election raised public awareness in America and elsewhere that the choice of voting technology is more than a mere technicality. Palm Beach County, Florida, demonstrated to the world that punch card ballots—a form of voting whereby voters punch holes in voting cards with a ballot marking device—are highly vulnerable to human error. As became evident, voters often fail to punch the cards cleanly, leading to the infamous ‘hanging chads’ that might have swayed the 2000 election to Bush (Brady et al. 2001 ). Awareness also grew about similar concerns with other common voting methods. For example, the optical scanners that are sometimes used for the counting of write-in ballots may not count a vote if the relevant boxes, bubbles, or arrows have not been marked in a sufficiently clear way (Kimball and Kropf 2005 ). More generally, voters may misunderstand the rules and, for example, vote for both a presidential and a vice presidential candidate in U.S. elections (Herron and Sekhon 2003 ).

In 2002, the U.S. government passed the Help America Vote Act (HAVA). As a result, billions of federal and state tax dollars were spent to update older voting technologies. Most election authorities opted for one of two technological innovations: precinct scanners and direct-recording electronic voting machines (DREs). Both, but especially DREs, came with the promise of minimizing “lost votes” due to malfunctioning voting technology and voter mistakes. Precinct scanners allow voters to have their ballot papers checked at the polling station before the casting of their votes. The most advanced implementations report both overvotes (i.e., if voters vote for more candidates or options than are allowed under the rules) and undervotes (i.e., blank votes), thus giving voters a chance to discover and correct potential mistakes (Brady et al. 2001 ; Kimball and Kropf 2008 ). However, voters often fail to pre-check their ballots (Hanmer et al. 2010 ). DREs, by contrast, automatize much of the error checking and prevention process. For example, many DREs do not just alert voters to overvotes, but prevent overvotes altogether. DREs also remove all problems related to unclear marking of the ballot because votes are cast by touching a screen or pressing a button. Similarly to precinct scanners, DREs can also be programmed to alert voters if they are about to skip a race (e.g., with a flashing light) (Alvarez and Hall 2008 ).

Have these technological fixes worked as intended? The election debacle in 2000 led to a flurry of new research into the relationship between voting technology and residual votes, much of it focused on the U.S. (for a review of this literature cf. Stewart 2011 ). However, aside from a general consensus that punch card systems often lead to much higher residual vote rates (e.g., Brady et al. 2001 ; Knack and Kropf 2003 ; Ansolabehere and Stewart 2005 ; Kimball and Kropf 2008 ; though also cf. Lott 2009 ), the findings from this literature have remained contradictory. To be sure, several studies report evidence that precinct scanners (e.g., Alvarez et al. 2013 ; Kimball and Kropf 2008 ) and DREs (e.g., Stewart 2006 ) tend to reduce residual vote rates, including (for the case of DREs) two studies conducted outside the U.S., one in Brazil (Fujiwara 2015 ) and the other in the Netherlands (Allers and Kooreman 2009 ). Particularly promising, Tomz and Van Houweling ( 2003 ) reported evidence from two U.S. states, Louisiana and South Carolina, that DREs significantly reduce the gap between African American and white voters in terms of voided ballots. However, other studies point in different directions. In a comprehensive study of the U.S. experience that covers the whole nation and elections from 1988 to 2000, Ansolabehere and Stewart ( 2005 ) find that DREs often produce more residual votes than traditional paper-based voting methods, such as hand-counted write-in ballots. Knack and Kropf ( 2003 ) come to a similar conclusion in their study of the 1996 U.S. presidential election, whereas Brady et al. ( 2001 ) find that DREs performed comparably to, but did not outperform, most paper-based voting systems in the 2000 U.S. presidential election (also cf. Lott 2009 ). Regarding precinct scanners, both Knack and Kropf ( 2003 , fn. 21) and Tomz and Van Houweling ( 2003 , p. 56) report no significant differences in residual votes when comparing them with centrally counted optical scanning systems that do not provide voters with the possibility to check their ballots.

These disparate findings can be partly reconciled when considering that precinct scanners and DREs are not all born the same. Not all versions of precinct scanners alert voters to undervotes, which could decrease their performance (Miller 2013 ). At the same time, especially older DREs tended to have usability issues, which could explain why some studies found few, if any, improvements over paper-based voting technologies (Stewart 2006 ). Kimball and Kropf ( 2008 ), for example, show evidence from the 2004 election in the U.S. that full-face DREs that display all ballots at once on sometimes massive screens can overwhelm voters and make it more rather than less likely that they miss down-ballot contests. In addition, the performance of voting technologies is likely to differ depending on context factors, such as the complexity of electoral rules, the design of paper ballots, and levels of education.

However, many prior studies also suffer from limitations that render their conclusions uncertain (Stewart 2011 ). Especially earlier studies often relied on cross-sectional variation in voting technology while accounting for potential confounders by controlling for factors such as the size and average income of electoral districts (e.g., Kimball and Kropf 2008 ; Knack and Kropf 2003 ; Tomz and Van Houweling 2003 ). However, this risks confounding the effects of voting technology with other differences across jurisdictions that are more difficult to measure, such as the sophistication of voters, election laws, or levels of voter disaffection. Other studies have relied on more sophisticated panel data designs (e.g., Ansolabehere and Stewart 2005 ), which allow to control for cross-sectional differences via fixed effects estimation. However, a problem that remains is that these studies tend to make comparisons across different elections with potentially different dynamics, such as presidential races or ballot measures in different states. This risks conflating the effects of voting technology with election-specific factors, such as the closeness of races or their perceived importance (cf. Keele and Minozzi 2013 ). Therefore, more (and better) evidence on the performance of different voting technologies is needed.

Internet Voting and Residual Votes

This study sheds new light on the causal effect of electronic voting technology on residual votes based on a case study of Geneva canton. While prior studies have focused on DREs, this study extends the focus to a different form of electronic voting: Internet voting. From the perspective of residual votes, DREs and i-voting systems are not too different, as error-prevention mechanisms available in the context of DREs are often easily extendable to online voting. However, whereas DREs are for voting in polling stations, i-voting extends error-prevention mechanisms to remote voters. The remainder of this section provides a short overview of the i-voting trials in Geneva canton, including a discussion of the ways in which Geneva’s i-voting solution could have reduced the residual vote rate.

Geneva’s Internet Voting Trials

Geneva canton ranges among the Internet voting pioneers. In 2002, the Swiss government decided to enable trials with online voting in selected cantons. Geneva took up the challenge, along with two other cantons (Neuchâtel and Zurich). In 2003, Geneva staged Switzerland’s first i-voting experiment in the context of a local-level referendum in Anières, one of its smaller municipalities. The following year, Anières and three other municipalities first used i-voting for federal (i.e., national) and cantonal (i.e., regional) referendums. I-voting experiments continued in subsequent years in these and other municipalities. The only exception was the period between June 2005 and June 2008, when Geneva’s i-voting program was temporarily suspended because of the need to establish a firmer legal basis. In 2009, online voting was extended to Swiss expatriates registered in Geneva canton, an option that has remained available to them since (Pammett and Goodman 2013 ; Serdült et al. 2015 ).

Against initial expectations, Internet voting proved only moderately popular with Geneva’s voters. As in most other i-voting experiments (e.g., in Estonia), online ballots were always offered as a complement to paper ballots in Geneva canton. However, more unusually, voters in Geneva always also had the option to vote by mail. Voting materials were always automatically sent to voters around 4 weeks prior to an electoral contest, and they could then choose whether to take their ballot papers to a polling station, whether to return them by mail, or, where that opportunity existed, whether to cast their votes online. Perhaps due to this highly convenient range of choices, on average only around 20% of votes were cast online where the opportunity existed (Mendez and Serdült 2017 ; Serdült et al. 2015 ). The only major exception were expatriate voters, 50% and more of whom tended to make use of the possibility to vote online (see Fig. 1 and, for further details, Germann and Serdült 2014 ).

Data source : Serdült et al. ( 2015 ), updated with official records

Internet voting usage in Geneva canton, 2004–2016.

Against the expectations of many, available evidence also suggests that the introduction of i-voting had no effect on electoral turnout (Germann and Serdült 2017 ). Again, a plausible reason is the availability of postal voting. Voting in Geneva is rather convenient even in the absence of online ballots. Where voters cannot also vote by mail, such as in Estonia or Canada, extant evidence suggests that online voting can provide a boost to turnout (Alvarez et al. 2009 Goodman and Stokes, forthcoming).

Electronic Safeguards Against Accidental Residual Votes

However, even if i-voting did not affect participation rates in Geneva canton, by reducing voter errors it might still have increased the effective turnout in terms of the number of valid votes cast. Next, I identify the safeguards implemented in Geneva’s i-voting solution that could have helped voters to avoid accidental residual votes. Given that Geneva’s i-voting trials were generally limited to direct democratic votes, the discussion (as the empirical analysis that follows) focuses on the case of referendum ballots. Footnote 2

Throughout the period analyzed (2001–2016), the same referendum ballots featuring ‘yes’ and ‘no’ boxes next to every measure were used in Geneva for both postal and the traditional ballot box voting. In order to cast a valid vote, voters had to check one of these boxes with a cross. Mail ballots were then counted centrally with optical scanners, whereas votes cast in polling stations were counted by hand in the individual polling stations. Footnote 3 As mail ballots were far more popular—often more than 90% or even 95% of paper ballots were returned by mail—most paper ballots were scanned. Neither mail nor precinct voters had access to any kind of technology, such as precinct scanners, that would allow them to check their marked ballots for errors.

Geneva’s i-voting system improves upon this system in two ways. First, it prevents accidental overvotes. In the context of referendum votes, the danger that voters erroneously conclude that they are supposed to check both the yes and no boxes is likely to be small. However, it is possible that voters leave stray marks covering the second box, which can prevent the optical scanners from deciphering a voter’s intention, leading to the invalidation of the vote. Footnote 4 Similarly, voters may come to realize that they did not give the answer they intended to give, leading them to check the second box while attempting to strike through (or erase) their original answer, which is not allowed. Geneva’s i-voting system prevents such unintentional overvotes because voters can choose their favored answer from a drop-down menu, which makes choices correctable and ensures that voters give one answer only.

Second, Geneva’s i-voting system is likely to reduce accidental undervotes. I-voting precludes undervotes that result from voters placing their checks outside of the relevant boxes. I-voting also precludes undervotes that result from voters using a red-colored pen, which cannot be read by Geneva’s optical scanners. Finally, and perhaps most importantly, the i-voting software makes it less likely that voters skip a race by accident. It is not uncommon in Switzerland that voters have to vote on 5, 10, or even more ballot measures at the same time (Selb 2008 ). When ballots are as crowded, the chance that voters unintentionally skip one or more of the proposals is likely to increase. While it is still possible to cast a blank vote with i-voting, it becomes less likely that voters do so unintentionally because online voters are shown a confirmation screen after completing their ballot. The confirmation screen prompts voters to review their choices before the final submission. Thus, undervoting becomes more transparent and correctable.

Empirical Strategy

Could these safeguards reduce the residual vote rate? The Geneva case enables a comparatively robust answer to this question because of its staggered adoption of i-voting over time and space.

Ever since the very first i-voting trials in Geneva canton, federal safety legislation has been in place limiting the number of voters who can participate in i-voting trials. The goal of this law has been to reduce the risk in terms of electoral manipulation. Initially, the safety legislation stipulated that not more than 20% of all voters in a canton should have access to online voting. In 2012, the cap was increased to 30% of a canton’s electorate. Footnote 5 To conform with this legislation, Geneva’s electoral administrators decided to trial i-voting only in selected municipalities. This way, they could ensure that the federally imposed cap would never be surpassed. There was some turnover over time, with some municipalities dropping out of the trials and others joining. But i-voting was always offered in some municipalities and not others. Notably, all voters in trial municipalities had the option of voting online. Trial municipalities were selected so that the federal cap would still be met if that were to happen. Of course, in practice only a minority of voters tended to make use of the possibility (see above), so that the actual number of online voters was consistently far below the federal cap. Importantly, trial municipalities were not selected randomly, but election officials sought to balance trial and non-trial municipalities on key socio-demographics (Germann and Serdült 2017 ). Table 1 shows that this strategy was partially (but not fully) successful when it comes to population size, age, education levels, and per capita income.

However, even if trial and non-trial municipalities are not fully balanced, the significant upshot of the way in which Geneva responded to the federal safety legislation is that there is both over-time and between-municipality variation in the availability of i-voting. As a result, municipalities from the same political unit, some of which had i-voting whereas others did not, can be compared while they simultaneously voted on the same issues. This set-up facilitates difference-in-differences estimation and, therefore, to straightforwardly account for any cross-sectional imbalances between trial and non-trial municipalities, such as, at least approximately, differences in income or education. Moreover, difference-in-differences estimation automatically takes care of any confounder that is specific to voting days or even ballot proposals, such as varying levels of voter disaffection or interest in referendum proposals. Beyond this, electoral laws apply uniformly across Geneva canton, thus ruling out bias due to variation in electoral legislation; and causal inference is facilitated further by Geneva’s relatively high social homogeneity (Geneva is commonly referred to as a “city canton” and 80% of its municipalities are counted as urban or peri-urban by the Federal Statistics Office).

Overall, the case set-up in combination with difference-in-differences estimation make it possible to rule out most possible confounders by design. However, difference-in-differences estimates are valid only if the parallel trends assumption is met (Angrist and Pischke 2009 ). In the present case, this means that under the counterfactual scenario where i-voting would have never been introduced, the residual vote rate should have evolved in parallel in treated (with i-voting) and control (without i-voting) municipalities. Further below I provide indirect evidence in favor of the parallel trends assumption. At the same time, I relax the parallel trends assumption via the inclusion of municipality-level time trends. Municipality-level time trends can increase our confidence that smooth changes in, for example, the socio-economic composition of municipalities do not bias the causal estimates. Moreover, all models control for electoral participation. While existing evidence suggests that i-voting had no measurable effect on turnout in Geneva canton (Germann and Serdült 2017 ), controlling for participation ensures that the estimated effects are independent of any small changes in turnout rates that cannot be safely distinguished from zero. In the robustness section I show that controlling for additional time-varying confounders does not affect the results.

Four further remarks are in order before turning to the empirical analysis. First, prior to 2001 Geneva canton used a different paper voting system whereby voters had to write ‘yes’ or ‘no’ next to referendum proposals rather than checking boxes. Also, prior to 2001 all ballots were counted manually, including mail ballots. Therefore, all analyses reported below focus on the period from 2001 onward.

Second, in late 2016 Geneva switched to a system whereby voters from all municipalities can i-vote if they register for an online ballot. To comply with federal safety regulations, registrations are capped at 30% of the canton’s electorate. Unfortunately, this implies that there is no longer between-municipality variation in i-voting availability. Given the absence of suitable control units, the analysis stops in September 2016, after which the new system was introduced.

Third, the federal safety regulation applies only to federal votes. Therefore, Geneva was in principle free to offer i-voting on a broader basis for its own, canton-level electoral contests. However, in practice cantonal referendums tend to be scheduled simultaneously with federal referendums, to profit from the latter’s higher turnout and save costs. As it would be impractical to offer i-voting for some but not other votes on the same ballot, the 20/30% cap therefore implicitly also applied to most cantonal referendums. There were only three exceptions to this general rule during the period studied. In May 2011, November 2011, and October 2012, no simultaneous federal referendums were scheduled and Geneva canton therefore allowed all its citizens to vote online in cantonal referendums. Given the lack of within-canton variation, there are no plausible counterfactuals in these cases. Therefore, I exclude all 11 cantonal referendums voted on these three dates. All other cantonal referendums are included.

Finally, as there are no plausible counterfactuals for municipal contests, I exclude all municipal referendums, even if they were voted simultaneously with federal referendums.

Availability of i-voting in Geneva canton, 2004–2016

Main Results

I proceed to estimate the causal effect of the availability of i-voting in a municipality on the number of residual votes. The sample covers all cantonal and federal referendums voted in Geneva canton between 2001 and September 2016, except for the aforementioned 11 cantonal referendums when i-voting was made available in all municipalities. Overall, the sample includes 284 referendums voted on 53 separate dates. The unit of analysis is a municipality voting on a referendum proposal. All 45 municipalities in Geneva canton are included. In addition, I include expatriate voters as a separate, artificial 46th municipality. The results remain similar when expatriate voters are dropped (see Table S1 in the Online Supplement).

The dependent variable is the residual vote rate, defined as the percentage of votes that do not enter the final count relative to the total number of votes cast. Footnote 6 The average residual vote rate in the sample is 5.3%. Footnote 7 The central explanatory variable is the availability of i-voting in a municipality. I-voting was available on 28 of the 53 voting days (156 of 284 referendums) in at least four and a maximum of 18 municipalities during the period studied (see Fig. 2 for breakdowns by municipality).

All estimates are based on OLS regression with municipality and referendum fixed effects. Standard errors are clustered by municipality to account for time dependence. Two-way fixed effects regression constitutes a generalization of difference-in-differences estimation for multiple time periods (Angrist and Pischke 2009 , pp. 233–241). The causal effect of the availability of i-voting is estimated solely based on within-municipality variation in the availability of i-voting and the residual vote rate. All models include quadratic municipality-level time trends and control for electoral participation. Footnote 8

The results suggest that Internet voting constitutes an effective method to reduce voter errors and uncounted ballots. As argued above, Geneva’s i-voting solution prevents overvotes and decreases the potential for unintentional undervotes (among other things because of the confirmation screen). Model 1 in Table 2 suggests that as a result of this, the residual vote rate decreased by an average of 0.32 percentage points if a municipality offered the possibility to vote online ( \(p < 0.001\) ). To get a better grasp of the magnitude of this effect, I compare the point estimate to the counterfactual numbers of residual votes had i-voting never been made available. This suggests that i-voting decreased the average residual vote rate from 5.4 to 5.1% in municipalities with i-voting, which corresponds to a 6% decrease. Expressed differently, i-voting increased the share of valid votes in an average referendum by 0.3%, from 94.6 to 94.9%. While not earth-shattering, an 0.3% increase in the number of valid votes—and, therefore, effective turnout—is notable in light of the fact that only around a fifth of voters tended to make use of online voting where that possibility existed. Also, survey evidence suggests that Geneva’s online voters tended to have comparatively high levels of education. In particular, online voters were almost twice as likely to have a university degree compared to paper voters (Sciarini et al. 2013 , p. 48). Therefore, Geneva’s online voters constitute a demographic that, a priori, should be less susceptible to voter errors. Footnote 9

Additional analyses reported in models 2 and 3 in Table 2 suggest that electronic safeguards against residual votes are especially important when it comes to cantonal (and, thus, down-ballot) measures. Specifically, I find that whereas i-voting decreased the residual vote rate by a mere quarter of a percentage point in federal referendums ( \(p = 0.04\) ), the reduction amounts to almost half a percentage point in cantonal referendums ( \(p < 0.001\) ). The most plausible explanation for this finding is the extra nudge to voters provided by the confirmation screen to review their choices before the final submission. Cantonal referendums may be more prone to oversight and accidental undervotes, first, because they are often seen as ‘second order’ and tend to receive less media attention (Buetzer 2011 ), and second, because they are placed towards the bottom of ballot papers. Footnote 10 Therefore, asking voters to confirm their choices may be more important when it comes to cantonal referendums.

Causal Identification Assumption and Robustness Checks

The central causal identification assumption is that the residual vote rate would have evolved in parallel in municipalities with and without Internet voting had Internet voting never been introduced. To assess the plausibility of the parallel trends assumption, I consider the evolution of the residual vote rate in the period before the first i-voting trial in September 2004. Figure 3 shows annual averages of the number of residual votes from 2001 to mid-2004 by treatment status. Municipalities with at least one i-voting trial in subsequent years are assigned to the treatment group. All others are assigned to the control group. As becomes evident, the residual vote rate follows a very similar trajectory in treated and control municipalities before the first i-voting trial. This is of course no direct test of the parallel trends assumption, which relates to a counterfactual and is therefore fundamentally untestable. However, evidence for parallel pre-treatment trends makes it plausible that the residual vote rate would have developed in parallel also after September 2004 had i-voting never been introduced, and hence that the reduction in residual votes attributed to i-voting has causal interpretation.

Pre-treatment trends (residual vote rate)

I provide additional, statistically-based evidence for the parallelism of pre-treatment trends based on a placebo test. To this purpose, I define a placebo treatment and code it 1 for all referendums voted on the 3 voting days before the first i-voting trial in a municipality, where applicable. I then estimate an analogous two-way fixed effects models including both the indicator for actual i-voting availability and the placebo treatment. As would be expected if pre-treatment trends are parallel, model 1 in Table 3 shows that the placebo treatment has no statistically significant effect on the residual vote rate ( \(p = 0.20\) ).

To further probe the internal validity of the results, I re-estimate the model while accounting for several additional municipality-level covariates that could plausibly affect the number of residual votes: per capita income, unemployment rate, population size (logged), age group shares (20–34; 35–49; 50–65; and 65+), the share of non-Swiss nationals, and vote shares for left-wing parties in the previous national election (lower chamber). Footnote 11 All data is drawn from official statistics. Data on the average income in municipalities is available only until and including 2015, so all referendums voted in 2016 are now dropped. Moreover, expatriate voters are no longer included because data on several covariates are unavailable (e.g., unemployment rate) or do not apply (e.g., share of foreigners). Further improving confidence in the estimated effect, model 2 in Table 3 shows that the coefficient for i-voting remains almost identical in both size (− 0.32) and statistical significance ( \(p = 0.002\) ). Similar conclusions are reached for this as well as all other robustness checks when disaggregating the sample into federal and cantonal referendums (see Tables S3 and S4 in the Online Supplement).

Next, I re-estimate the treatment effect while dropping cases with simultaneous municipal elections or referendums (see model 3 in Table 3 ). Simultaneous municipal electoral contests are rare—less than 1.5% of observations are concerned—and most municipal electoral contests are low-key affairs, similarly to cantonal referendums. Still, some municipal contests may mobilize additional voters, leading to potential violations of the parallel trends assumption. Reassuringly, the effect of i-voting on the residual vote rate remains virtually unchanged when dropping observations with simultaneous municipal contests.

Finally, I re-estimate the treatment effect while clustering standard errors by municipality and voting day. This adjusts standard errors for contemporaneous dependence among referendums voted on the same day, in addition to time dependence (Cameron et al. 2011 ). I find that the variance estimate remains similar ( \(p = 0.005\) ) (see model 4 in Table 3 ), including when estimating separate models for cantonal ( \(p = 0.001\) ) and federal ( \(p = 0.08\) ) referendums (see Tables S3 and S4 in the Online Supplement).

Indirect Effect on Electoral Outcomes?

Having established the robustness of the causal estimate, I finally turn to the question whether the reduction in the residual vote rate affected the outcomes of referendums in Geneva canton. As noted in the introduction, prior evidence suggests that voting errors are disproportionately committed by voters with low educational attainment (Bullock and Hood 2002 ; Tomz and Van Houweling 2003 ). Therefore, an important hope associated with error-reducing voting technologies has been that they reduce education-based disparities in uncounted ballots and can thereby improve the representation of less educated voters (Knack and Kropf 2003 ; Tomz and Van Houweling 2003 ). In line with this, Fujiwara ( 2015 ) found evidence that the introduction of DREs in Brazil increased electoral support for policy proposals that directly benefit voters with low education, such as economic redistribution and a strong welfare state, as well as support for left-wing parties more generally. However, whether such findings generalize to the case of Internet voting is not clear, especially as online voting is less frequently used by voters with low levels of education (Serdült et al. 2015 ).

To investigate potential knock-on effects on electoral outcomes I repeat the estimation set-up from above while switching the dependent variable from the residual vote rate to direct-democratic policy choices made by Geneva’s voters. As above, all models control for electoral turnout so as to make sure that the measured effect of the availability of i-voting reflects the implications of the reduction in uncounted ballots. Footnote 12 Table 4 shows the results.

I consider a total of four dependent variables. The first two enable me to investigate whether the reduction in uncounted ballots shifted referendum outcomes systematically to the left (or right). These measures leverage the fact that parties in Switzerland almost always publish voting recommendations prior to referendums. Using this information I coded two variables that, respectively, record the share of valid votes cast in favor of the options recommended by the Socialists (the largest left-wing party in Geneva canton) and the Greens (the second-largest left-wing party). For example, the first variable records the vote share in favor of a proposal if the Socialists recommended a ‘yes’ vote, and the no share if the Socialists recommended a ‘no’ vote. Models 1 and 2 in Table 4 show that the introduction of i-voting, conditional on turnout, had no statistically significant effect on levels of voter support for policy proposals favored by left-wing parties ( \(p = 0.45\) and 0.92, respectively). This suggests that the reduction in residual votes did not pull electoral outcomes towards the left (or the right).

Next, I analyze whether i-voting more specifically affected voter support for economic redistribution. To test this I manually identified referendums with direct implications for the level of economic redistribution from richer to poorer citizens. I was able to identify 66 relevant referendums. Footnote 13 I then used these 66 ballot proposals to code a variable recording the share of valid votes for increased redistribution. The variable corresponds to the yes share if a proposal would increase redistribution (e.g., a 2014 proposal for a federal minimum wage) and the no share for proposals that would lower redistribution (e.g., a 2002 proposal to cut unemployment benefits). Again, I find no evidence for an indirect effect on referendum outcomes (see model 3 in Table 4 ).

As elsewhere in Western Europe, the working class in Switzerland has increasingly turned to right-populist parties advocating culturally conservative policy proposals (Oesch 2012 ). As a final step, I therefore consider whether i-voting affected support for nativist policy proposals, such as a 2014 proposal to cut “mass immigration”, as well as other proposals generally associated with the cultural conservatism to cultural liberalism continuum, such as European integration, law and order, gay rights, and abortion (cf. Kriesi et al. 2006 ). I found a total of 38 relevant referendums during the period studied, and coded an analogous variable recording the share of valid votes in favor of cultural conservatism. Footnote 14 This variable records the yes share if a proposal would lead to more cultural conservatism (e.g., the previously mentioned proposal to cut immigration) and the no share if a proposal would lead to less cultural conservatism (e.g., a 2005 proposal to grant foreigners the right to vote in municipal elections). Again, I find no evidence that the reduction in residual votes affected referendum outcomes (see model 4 in Table 4 ).

Pre-treatment trends (referendum outcomes)

Figure 4 plots average vote shares for left-wing parties as well as support for economic redistribution and cultural conservatism prior to the first i-voting trial. It becomes visible that the different dependent variables evolved approximately in parallel in treated and control municipalities. Footnote 15 All four models also pass placebo treatment checks (see Table S7 in the Online Supplement). Footnote 16 Analogously to above, this can be seen as supporting the parallel trends assumption and, hence, that the effect estimates have causal interpretation. Tables S8 and S9 in the Online Supplement show that the results remain unchanged when controlling for additional time-varying covariates and when dropping observations with simultaneous municipal contests. Finally, I also find no effects on electoral outcomes when disaggregating the sample into cantonal and federal referendums (see Tables S10 and S11 in the Online Supplement). This rules out an indirect effect that is visible only for cantonal referendums, which tend to see larger reductions in the residual vote rate.

Overall, these results suggest that i-voting’s reduced error potential remained without systematic implications for the outcomes of referendums and, in particular, that the introduction of i-voting did not improve the policy representation of voters with low education. As noted, a possible explanation is that online voting is most popular with highly educated voters, which could offset any effect on the representation of less educated voters. For such an effect to materialize, more voters with low education may have to make use of the opportunity to vote online. That said, it is important to note that the estimated coefficients represent average effects. One cannot, therefore, infer that the reduced error rate did not affect the outcome of any given referendum.

Uncounted ballots rarely make headlines. But the number of votes that are discarded from the tallying of final results can run into the tens of thousands and, in large polities, the hundreds of thousands. This study presented new evidence that Internet voting systems can prevent voters from accidentally casting residual votes. The estimated effects—an 0.25 percentage points reduction in the residual vote rate for federal referendums and almost 0.5 percentage points for cantonal referendums—may seem modest and some prior studies, if often based on less robust research designs, reported larger effects for similar comparisons. Stewart ( 2006 ), for example, presented evidence that U.S. counties that switched from central count optical scan systems to DREs after the 2000 election reported an 0.7 percentage points reduction in the residual vote rate in the 2004 presidential election. Extending the focus to referendum ballots, Kimball and Kropf ( 2008 ) report a similar effect size for touch-screen DREs. Footnote 17 However, the estimates from these studies refer to situations in which most, if not all, voters made use of electronic voting. By contrast, the estimates from this study refer to a situation in which only a fifth of votes were cast electronically (i.e., online), and the rest by paper.

Therefore, despite the relatively small effect sizes, this research suggests that electronic voting systems provide an effective remedy against common mistakes made by voters. What is more, this study also points to a way how error-reducing voting technology can be extended to remote voters. Countries around the globe increasingly allow voters to cast their votes remotely, most typically by mail (Gronke et al. 2008 ). However, only voters who frequent a polling station can profit from error-reducing technologies considered in prior studies, including DREs and precinct scanners (Alvarez et al. 2013 ). A unique benefit of Internet voting is that it allows the extension of technological safeguards against accidental residual votes to remote voters.

Nevertheless, the results of this study cannot, and should not, be read as a blanket recommendation of Internet voting (or electronic voting more generally). One of Internet voting’s weak points is that it tends to appeal more strongly to more educated (and younger) citizens. While that may change in the future (Vassil et al. 2016 ), all voters should be able to profit from safeguards against errors. If a polity wants to enable remote voting, that could, for example, suggest a combination of Internet voting with DREs. However, proneness to accidental residual votes is not the only criterion by which voting technologies should be judged. There are, in particular, increasingly concerns about the vulnerability of electronic voting systems to third party manipulation and consequent risks to the integrity of elections. As decisions on voting technology should not be based on their proneness to residual votes alone, no clear recommendations can follow from studies of residual votes, such as this one.

At the same time, this remains a single case study. Case constraints prevented me from analyzing residual votes in elections. Most paper votes in Geneva canton are also counted with optical scanners while in other contexts paper ballots are hand-counted. Based on a priori reasoning, there seem to be few reasons why the results of this study should not generalize to elections and to manual counting. Many kinds of elections have decidedly more complex rules than yes/no referendums and, therefore, more potential for voter error. And, while some of the issues that can emerge with optical scanners, such as stray marks, may be less of a problem if ballots are hand-counted, paper ballots remain difficult to correct; and irrespective of the counting method cannot alert voters to undervotes or prevent overvoting. Nevertheless, to move beyond conjecturing, more empirical evidence from other case contexts is needed.

Beyond cross-validation, an important contribution of future studies could be to identify the most effective technological safeguards against residual votes. For example, Geneva’s online voting system prompts voters to review their choices via the inclusion of a confirmation screen. Could accidental residual votes be reduced more effectively if voters were in addition given explicit reminders that they are about to undervote? And what if they were shown contests sequentially rather than all on the same screen, as is the case in Geneva canton? Finally, we also need more comparative evidence on the performance of electronic voting systems relative to other measures against accidental residual voting. For example, are electronic voting systems or precinct scanners more effective in reducing residual votes? Or, are improvements in paper ballot design or voter education campaigns more effective responses? While the existing literature has few answers to these questions, providing them will prove useful to electoral administrators around the world.

Data Availability

The data and code required to replicate all analyses in this article are available on the journal’s Dataverse within the Harvard Dataverse Network ( https://doi.org/10.7910/DVN/01F70K )

As is explained below, paper voters had no access to technology, such as precinct scanners, that could have helped them to spot errors.

For almost a decade Geneva offered i-voting exclusively in the context of referendums. In 2012, i-voting was first offered in the context of a cantonal election for Geneva’s Court of Auditors. However, i-voting remained unavailable in most subsequent elections. Therefore, the total number of elections conducted online in Geneva canton remains too small for meaningful statistical analysis.

Between 2010 and 2012 the canton replaced the scanners used prior to this with a new, quicker model from the same company (Axiome). According to electoral administrators, the older and the new models had the same functionality, apart from speed.

Stray marks constitute less of a problem for the minority of paper ballots that are counted manually.

Since 2014, federal legislation allows the extension of i-voting to 50% or even all voters in a canton if advanced security requirements are met, such as universal verifiability. However, at the time of writing Geneva’s i-voting system did not meet these requirements.

Geneva’s electoral statistics do not clearly separate under- from overvotes. While undervotes always figure as ‘blank’, overvotes can figure as both ‘blank’ or ‘invalid’, depending on the circumstances (cf. articles 64 and 65A of Geneva’s ‘loi sur l’exercice des droits politiques (LEDP) [law on the exercise of political rights]’). Unfortunately, this makes it impossible to determine the extent to which the aggregate effects reported below are due to reductions in over- and undervotes, respectively.

Note that this figure includes a considerable number of intentional undervotes. According to post-referendum surveys (Kriesi et al. 2018 ), on average around 3% of Swiss voters intentionally cast a blank vote on a ballot proposal during the period under study. The most likely reason is lack of interest in some of the less salient proposals on a ballot. Usually less than 0.5% of Swiss voters reported to have cast a blank vote on each and every proposal on the ballot. The corresponding figures for Geneva canton cannot be established due to sample restrictions.

The results remain almost identical when dropping turnout from the list of controls (see Table S2 in the Online Supplement).

Internet voters in Geneva also tended to be younger than the average voter (Sciarini et al. 2013 , p. 29; Serdült et al. 2015 ), but age is a less likely determinant of accidental residual votes.

Conforming with these arguments, cantonal referendums have a higher residual vote rate compared to federal referendums (3.6% versus 6.9%). However, note that voters are also more likely to selectively abstain from cantonal referendums due to lack of interest or higher information costs.

Unfortunately, municipal-level data on education levels is unavailable beyond the year 2000 due to a change in census data collection practices. However, the control for per capita income should at least partly make up for this. It is also worth noting that per capita income is far from statistically significant ( p = 0.38).

However, the results are again similar in models that do not control for turnout (see Table S6 in the Online Supplement).

Table S12 in the Online Supplement lists all referendums used to measure ‘support redistribution’, including short descriptions of the policy proposals.

Table S13 in the Online Supplement lists all referendums used to measure ‘support cultural conservatism’.

As above, municipalities are considered ‘treated’ if its citizens had the opportunity to i-vote at least once after September 2004, and as ‘control’ if citizens never could i-vote.

As above, the placebo treatments are coded 1 for the 3 voting days before the first i-voting trial in a municipality.

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Acknowledgements

Earlier versions of this paper were presented at the ECPR General Conference at the University of Wroclaw (2019), the Three Countries Congress at ETH Zurich (2019), the Elections, Public Opinion, and Parties Conference at Royal Holloway, University of London (2018), and a seminar at the University of Bath (2018). I am especially grateful to John Curtice, Anja Giudici, Kostas Gemenis, Silke Goubin, Sophia Hatzisavvidou, Fernando Mendez, Penny Miles, Uwe Serdült, Rodney Smith, Jennifer Thomson, Katerina Vrablikova, Jonathan Wheatley, and four anonymous reviewers for valuable comments and criticisms. A big thank you also goes to the Chancellerie d’État of the canton of Geneva for their patient answers to my repeated queries regarding the voting process in Geneva canton.

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Germann, M. Making Votes Count with Internet Voting. Polit Behav 43 , 1511–1533 (2021). https://doi.org/10.1007/s11109-020-09598-2

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A Systematic Literature Review and Meta-Analysis on Scalable Blockchain-Based Electronic Voting Systems

Mohd juzaiddin ab aziz, zarina shukur, hafiz adnan hussain.

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Received 2022 Aug 15; Accepted 2022 Sep 29; Collection date 2022 Oct.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/ ).

Electronic voting systems must find solutions to various issues with authentication, data privacy and integrity, transparency, and verifiability. On the other hand, Blockchain technology offers an innovative solution to many of these problems. The scalability of Blockchain has arisen as a fundamental barrier to realizing the promise of this technology, especially in electronic voting. This study seeks to highlight the solutions regarding scalable Blockchain-based electronic voting systems and the issues linked with them while also attempting to foresee future developments. A systematic literature review (SLR) was used to complete the task, leading to the selection of 76 articles in the English language from 1 January 2017 to 31 March 2022 from the famous databases. This SLR was conducted to identify well-known proposals, their implementations, verification methods, various cryptographic solutions in previous research to evaluate cost and time. It also identifies performance parameters, the primary advantages and obstacles presented by different systems, and the most common approaches for Blockchain scalability. In addition, it outlines several possible research avenues for developing a scalable electronic voting system based on Blockchain technology. This research helps future research before proposing or developing any solutions to keep in mind all the voting requirements, merits, and demerits of the proposed solutions and provides further guidelines for scalable voting solutions.

Keywords: Bitcoin, Blockchain, cryptography, electronic voting, ethereum, Internet of things, hyperledger fabric, smart contract, scalability

1. Introduction

In many countries, technology plays a significant role in elections, which is necessary for some circumstances, such as the technology utilized to construct voter records, establish electoral boundaries, manage and educate employees, print ballot sheets, carry out voter education programs, cast ballots records, tally the votes, and compile and broadcast election results, to name a few. Technology can improve election organization, lower long-term expenses, and enhance political accountability if uses it correctly [ 1 ]. The technology used in elections can be as old as printing presses, ballpoint pens, or modern technologies such as computers and optical scanners, digital mapping, or the Internet; or it can be a mix of the two [ 1 , 2 ]. Organizing large-scale elections in countries without access to modern technologies can be difficult. It might change if Blockchain technology is the foundation for the electronic voting system.

For the sake of fostering public confidence and accountability among voters, electoral integrity is necessary not only in democracies but also in all societies [ 3 , 4 ]. From the government’s perspective, electronic voting technologies have the potential to boost voter participation and trust, as well as reinvigorate interest in the voting process. According to a new study, adopting electronic voting methods may improve security [ 5 , 6 , 7 ]. When deciding whether or not to utilize an electronic voting structure, it is necessary to research the factors that contribute to the system’s advantages over traditional voting methods, such as using paper ballots [ 8 ]. It is anticipated that it will improve the efficacy and efficiency of democracy; moreover, it will provide a solution to various highlighted problematic conditions. Likewise, it enhances election accessibility, lets the elderly and disabled vote, increases election turnout, and is simple to use while obtaining a quick result [ 9 ]. However, it is widely acknowledged that running electronic voting systems underneath tight security measures is essential, especially when using modern encryption methods [ 10 ]. In the beginning, electronic voting was proposed as a remedy to the issues caused by voting on paper ballots to ensure that elections would be fair and accessible [ 3 ]. Electronic voting system security problems have been widely researched in the literature. According to the findings of the research [ 11 , 12 ], electronic voting may present several challenges, including those related to data integrity, dependability, transparency, ballot secrecy, security, implications of fraud, repercussions of failure, ignorant voters, lack of special information technology skills, equipment storage, and cost.

Blockchain is a novel technology with much potential for information systems. Blockchain-based techniques are being researched in various fields, including healthcare, logistics, finance, etc. [ 13 ]. Electronic voting is becoming a more essential and widespread issue in the context of Blockchain and information systems. The unique characteristics of this technology, such as decentralization and immutability, were crucial in ensuring that the voting system followed the same norms as more conventional elections and voting fields [ 14 ]. This line of inquiry has gained traction recently due to rising allegations of electoral fraud, such as those levelled during the presidential election in the United States [ 8 ]. Democracy is founded on voting and will not work well if people do not trust the voting system.

On the other hand, it just takes a rumour to completely undermine people’s faith in a voting system, particularly an automated one. Conventional voting methods based on a paper presented a severe health risk during the COVID-19 outbreak; hence, the need for research on methods of electronic voting that are secure, impartial, and confidential became even more pressing [ 15 , 16 ]. Electronic voting systems’ reliability, speed, and security are not yet at a level that can boost the voter’s trust. Researchers are working on methods and procedures for a more secure and efficient electronic voting system to ensure anonymous voting is conducted in a fair and risk-free environment [ 17 ]. The implementation of Blockchain technology in voting systems has a reasonable chance of drawing the attention of researchers searching for the most effective solutions. Protocols can be implemented in a voting system to ensure that voting is conducted in a way that is private, public, and impartial [ 1 ]. Because of this, people’s trust in voting systems and democracy, in general, may increase.

Blockchain technology was the first and primarily used technology behind Bitcoin to keep track of financial transactions [ 18 , 19 ]. However, new proposals and applications have evolved in the past. Recently, the Blockchain-based electronic voting system has grown in importance to overcome some problems that might arise when voting electronically. Due to the immutable nature of the Blockchain, it has transformed into a decentralized and distributed voting system [ 20 ]. Consequently, Blockchain’s voting systems have been proposed as the next generation of electronic voting systems [ 21 , 22 ]. Because of Blockchain technology, governments are being driven to design voting systems that are both intelligent and bearable and incorporate information on sustainability into such voting systems. It ensures that all relevant parties access reliable information on long-term assets [ 23 ]. It is worth noting that even though Blockchain is increasingly being used to improve electronic voting system security, many difficulties remain in obtaining the full benefits from Blockchain. Identifying which problems should be addressed in designing a Blockchain-based voting system is required [ 24 ].

This research reviewed the literature and clarified such issues using a systematic mapping technique for this goal. This paper makes the following contributions: Identifying well-known proposals for scalable Blockchain-based electronic voting and their verification methods, and highlighting those proposals that used famous cryptographic solutions and their focus on cost and time. It also identifies performance parameters, the primary advantages and obstacles presented by different systems, and the most common approaches for Blockchain scalability. In addition, it outlines several possible research paths for developing a scalable electronic voting system based on Blockchain technology.

According to this study, Blockchain-based voting systems may solve data tampering and integrity problems. The most often expressed concerns with Blockchain voting systems are privacy, transaction speed, and scalability, which still need more work [ 25 , 26 ]. This article provides a systematic literature review of the motivations, research accomplishments, and applications intended to facilitate the integration of Blockchain and the electronic voting system. The main contributions are as follows:

We describe the research methodology and a literature evaluation on scalable Blockchain-based electronic voting;

We introduce the background knowledge of electronic voting and Blockchain technology from the perspective of scalability, summarized in the previous work. The motivations and benefits for applying Blockchain to electronic voting are discussed in terms of requirements and challenges in electronic voting and the characteristics of Blockchain;

We summarize an optimized research framework according to the Blockchain architecture, including the scalability aspect of Blockchain and horizontal and vertical scalability trilemma in Blockchain, and analyse and specify significant characteristics of Blockchain scalability;

As for the Blockchain applications in electronic voting, we reviewed the previous work on electronic voting based on Blockchain and focused on scalability;

We analysed the previous research by following our methodology to answer the required questions regarding Blockchain function/performance requirements for electronic voting by comparing different Blockchain project implementations to provide a reference for practitioners;

Finally, some open issues and challenges in the field of the electronic voting system, combined with Blockchain, are highlighted, such as shading, consensus algorithm, block size increase, directed acyclic graph, forking, and an increase in authorized hardware devices to decrease block generation rate;

This study was performed by PRISMA (preferred reporting items for systematic reviews and meta-analyses) [ 27 ]. It included Kitchenham’s [ 28 ] standard criteria to customize this SLR to the computer science area.

The rest of this paper is systematized, as depicted in Figure 1 . Section 2 demonstrates an overview of electronic voting and Blockchain technologies. Section 3 debates the previous research closely related to scalability in Blockchain for electronic voting. Section 4 discusses SLR methodology. Section 5 focuses on our methods’ results and categories per the defined methodology. Research challenges and future directions are addressed in Section 6 . In the end, we conclude this paper in Section 7 .

Road map of Blockchain-based electronic voting.

2. Background Knowledge

This section is separated into the theoretical bases of Blockchain technology and electronic voting. A separate team is dedicated to discussing these characteristics in further detail.

2.1. Electronic Voting

Electronic voting is a method of voting in a political election or referendum that uses electronic technology in the voting process, as per the European Council [ 29 ]. It includes specialized electronic voting machines:

Optical scanning;

Electronically printed ballots;

Centralized and decentralized software or applications for voting through the Internet;

To register voters, electronic voting machines make use of a variety of input devices. Some examples of these devices include keyboards and touch screens [ 30 ]. Paper trails, also known as voter-verified audit trails, are printed copies of recorded votes often presented for verification with the ballots themselves (VVAPTs). These devices are used for fast vote counting and collecting voter data. They also enhance ballot presentation, lowering the frequency of spoiled votes [ 29 , 31 ]. Some authors [ 32 , 33 ] believe that third parties, on the other hand, design specialized voting devices, making end-to-end verification rugged and lowering confidence in them. The optical scanners can scan and record votes on readable paper ballots. This method is simple to learn and provides quick and accurate results. In addition, this method utilizes paper ballots, which have not been tampered with but can be replaced and are very expensive to adopt and maintain [ 34 ].

Electronic ballot printers provide legible paper recipes or voting tokens that may be thrown away in vote boxes and counted by machines. Because of the tangible evidence, this strategy is transparent and provable [ 35 , 36 ]. However, this method is similarly costly, and the only benefit it has over the old voting system is that it prevents ballots from being spoiled. There are two main types of Internet voting software: centralized and decentralized. Both systems enable voters to cast their votes via electronic devices linked to the Internet [ 37 ]. This approach may take various forms, including specialized gadgets and web pages. Voting makes it easier for individuals to acquire rapid and precise results and makes voting more convenient [ 38 ]. Unfortunately, this mode of voting has the most severe security weaknesses, such as the potential for hacker attacks, inadequate anonymity and privacy, and the possibility of being forced to vote a particular way [ 39 ]. Two qualities may be used to classify electronic voting systems:

Remoteness;

Supervision.

Remoteness describes how the votes are transmitted for aggregation and counting. The votes are sent to a central counting authority in real time by a remote system using a communication medium such as the Internet [ 40 , 41 ]. On the other hand, a nonremote method gathers votes on the local level and then transmits them to a counting authority after the election has concluded [ 42 ]. The place of voting is determined by supervision. In a monitored system, votes may only be cast under the supervision of some authority, such as a polling station [ 43 ]. A nonsupervised method, on the other hand, permits people to vote from any place and cast their ballots. Electronic voting aims to enhance the conventional voting method by decreasing and controlling fraud, reducing human involvement, and speeding up result processing [ 44 , 45 ].

Moreover, expenses are lowered by concentrating on voting overhead and improving participation in democratic procedures by utilizing new technologies that are more accessible and useful [ 42 ]. Electronic voting methods, on the other hand, are not without flaws. The following are the most common issues that such systems face:

Insufficient clarity and comprehension of such systems on the part of non-experts;

An absence of standards and norms;

Threats posed by system suppliers, malevolent users, and privileged insiders and the potential for these individuals to attack and manipulate the system;

Cost increases due to required information and communication technologies (ICT) such as infrastructure, maintenance, and power consumption;

Various ways are used to address the issues in electronic voting, each using a distinct set of technology and algorithms. Blockchain technology has received much attention recently, and its potential for improving electronic voting systems has been acknowledged by [ 46 ]. The following parts will reveal the findings of this potential investigation.

In voting systems that use electronic equipment, ballots are either recorded or counted electronically. The term “electronic voting” refers to a voting process aided by computer gear and software. Such systems may handle various operations, from planning elections to storing vote ballots [ 47 , 48 ]. Laptops, tablets, and smartphones all fall under system types. The electronic voting system should contain voter registration, identification, voting, and tallying features.

The electronic voting system comprises the following processes: The first step is to create a voter registration list (registration). On election day, officials examine voters’ credentials (verification and authentication). People qualified to vote in the next phase may do so (casting collation). Encrypted and verified voting should be implemented in [ 49 ]. The votes must be kept secret, anonymous, and correct, and they cannot be changed or deleted [ 50 , 51 ]. Eventually, computerized voting systems can calculate votes simply by adding them by design (counting the presentation of results).

In general, computerized voting applications rely heavily on central authority control. Such systems have several flaws and hazards associated with them [ 52 ]. A few examples are the lack of electronic voting system norms, security and dependability risks, exposure to hacking, fraud susceptibility, malicious software development, machines’ high prices, and transactions’ safe storing [ 53 , 54 ].

The United States of America pioneered the usage of electronic voting in other countries in the year 2000, followed by France (2001), the United Kingdom (2002), Spain (2003), Ireland (2004), Estonia (2005), Portugal (2005), the Netherlands (2004, 2006, 2007), Paraguay (2008), Finland (2008), Austria (2009), Germany (2009), and Norway (2009) [ 3 ]. Estonia became the first country to employ electronic voting from a distant location in its national parliamentary elections of 2007 [ 55 , 56 ]. It came after the government used the technology in more limited legislative polls in 2005.

There are various voting methods available, each with its advantages and disadvantages. The most commonly used voting methods discussed in [ 57 ] are direct-recording electronic (DRE), punch card, public network DRE, kiosk voting, central count, and precinct count. It is essential to highlight that the characteristics listed in Table 1 should be included in all electronic voting systems.

Electronic voting system requirements.

2.2. Blockchain Technology

Blockchains are immutable distributed ledger systems that store data in a digital ledger without a central point of authority and failure. The defined consensus algorithm confirms every transaction on the public ledger on the system. Once a transaction has been made, it can never be changed [ 58 ]. Every node on the system is accountable for checking and verifying the system’s published data [ 59 ]. A platform made on Blockchain runs continuously on a peer-to-peer (P2P) network [ 60 ]. Anyone can connect to that network and receive incentives for running their software as a node. The first people who described and worked on the cryptographically connected chain of blocks were Stuart Haber and W. Scott Stornetta [ 61 ] in 1991. After that, in 1992, Bayer, Haber, and Stornetta [ 62 ] included Merkle trees in the design to increase the efficiency of collecting several documents into one block. The primary goal was to create a timestamp for digital copies to prevent manipulation. Satoshi Nakamoto [ 18 ] constructed the first Blockchain-based system in 2008. It is also important to point out that the cryptocurrency Bitcoin was the first prominent use of Blockchain technology [ 63 ]. The idea may be compared to a globally distributed open and secure data book. As a result, this technology may be used in the cryptocurrency and financial industries and other disciplines involving the transactions [ 64 ]. As a result, the idea is increasingly seen as a critical part of industry 5.0 applications in the future years. Although the Blockchain is famous in cryptocurrency, it is not unreasonable to believe that its possibility extends further to the digital currency [ 65 ]. Private companies and government institutions are also testing Blockchain [ 66 , 67 ].

“Blockchain” refers to a series of timestamped and cryptographically connected blocks. As other blocks are added, the total number of blocks in the chain will grow; the hash of the first block will be included in each subsequent block, as shown in Figure 2 . Blockchain protects either secret or general data from being tampered with or manipulated [ 68 ]. The Blockchain is nothing more than a decentralized ledger that records all the direct transactions between users and vendors inside the system—a distributed network of nodes that maintains a shared transaction source [ 69 ]. The nodes are in charge of validating these transactions. As a result, the Blockchain enables trust to be established without a central authority [ 70 ].

Model of a Blockchain data structure.

Some have considered that Blockchain technology could ultimately be more significant than the Internet. Blockchain technology agrees that the data be saved and swapped on a peer-to-peer (P2P) network. Structurally, the Blockchain data can be conferred, shared, and linked with consensus-based algorithms [ 71 ]. It is decentralized, and there is no requirement for “trusted third parties” or mediators to be present along with the procedure [ 72 ]. The technology behind the Blockchain serves as the foundation for the new kind of Internet. Blockchain is derived from two theories: asymmetrical cryptography, which provides the use of a matched public and private key system, and distributed information technology architecture (especially P2P) [ 73 ].

Asymmetric cryptography is used in Blockchain systems, which is a slower kind of encryption than the symmetric cryptography [ 66 ]. A distributed system has components on various networked computers, which share and coordinate their activities by passing messages to each other. Asymmetrical cryptography allows users who do not know each other to transmit encrypted data [ 74 ]. This approach sends encrypted data to a third party using a public key that may be shared with anybody [ 75 ]. The third party decrypts the data using a private key associated with the public key. In other words, a public key is like a bank account number that anyone can share [ 76 ]. When users log onto their bank account, they must use the same password to access the private key [ 77 , 78 ]. Bitcoin was the first use of Blockchain technology. It is a digital currency based on Blockchain technology and can be used to deal online in the same manner as using money to trade in the natural world [ 79 ]. Because of the success of Bitcoin, Blockchain technology may be used in various industries and services, including financial markets, IoT, supply chains, voting, medical treatment, and storage.

Blockchain technology is broadly used in our daily lives, such as cybercrime, travel, healthcare, finance, and education. The technological community is also discovering other potential uses for this technology in other fields [ 80 ]. Applications such as insecurity, settlements, finance and assets management, banking, industries, and insurances are being used and evaluated by [ 81 ]. The Internet has modified how we share information and connect; the Blockchain will change how we exchange value and whom we trust. Many people in the Blockchain industry have noticed that Blockchain has become overhyped [ 82 ]. The technology has some limitations and is inapplicable for many digital interactions [ 83 ].

Current electronic voting technologies and solutions are unreliable, insecure, and hazardous. Blockchain technology in the electronic ballot has attracted many academics looking for considerably efficient methods and protocols for an electronic voting system that can perform safe, anonymous, and fair voting [ 84 ]. As a result, faith in electoral systems and democracy may grow. On the other hand, Blockchain-based solutions face several difficulties. As technology becomes more extensive and complex, it becomes more challenging to scale a Blockchain network [ 85 ]. This vulnerability affects small and large networks since there are only a small number of nodes, and a large amount of computing power is concentrated on specialized hardware [ 86 ]. Other attacks are also feasible, such as denial of service, Sybil, and man in the middle.

Last but not least, it is essential to note that anonymity is not automatically achieved by using systems based on Blockchain technology [ 87 ]. Because every node has access to a leading Blockchain network, transactions can be tracked to identify the primary owners of that transaction [ 88 ]. However, it is essential to mention that the noted obstacles (and benefits) are broad and may not involve every technological deployment.

There are other methods to classify Blockchain-based systems, but the most frequent one is based on the rights granted to users and nodes. These permits include:

The ability to write;

The ability to read.

Writing rights in a Blockchain network determine who is eligible to act as a node and take part in the storage of the Blockchain data structure, the negotiation of its scopes as parts of a consensus mechanism, and the distribution of mining rewards. Participants in the Blockchain must go through this procedure to agree on the field’s information [ 89 ]. Permissionless Blockchain networks allow anybody to act as a node and have full public access to these privileges. The phrase “permissioned Blockchain network” refers to a system in which only a few people can edit the ledger. On the other hand, read rights define who has access to a Blockchain’s data and under what circumstances [ 90 ]. These rights distinguish between public Blockchain networks, which enable anybody to read their contents, and private Blockchain networks, which allow only a limited number of organizations to view their contents [ 91 ]. Blockchain technology is evolving and improving all the time. There are several implementations available, each with its own set of attributes.

2.3. Scalability Aspect of Blockchain

Scalability means more transactions for the same hardware in this context, specifically the ability to increase the volume of transactions per second. Although Blockchain has seen substantial acceptance in recent years, one of the primary problems that may restrict its role as a disruptive technology is the scalability of Blockchain-based solutions [ 12 ]. As a result, this study aims to explore and assess existing initiatives to improve Blockchain scalability in electronic voting systems [ 92 ]. Our study has led us to conclude that scalability is a broad concept with various meanings in the literature. As a result, we use a definition of scalability from recent research to describe scalability in the context of this study, where scalability might relate to:

Horizontal: This is accomplished by adding/increasing the number of computers in an existing pool/network;

Vertical: This is accomplished by adding more power (such as memory, processing, and storage-efficient approaches) to an existing pool of resources. As a result, these core notions have been employed to describe scalability in Blockchains.

This study researched prior Blockchain scalability research, such as those mentioned in current surveys on Blockchain scalability and the fundamental scalability principles accessible in contemporary literature [ 93 ]. As a result, this section analyses and specifies significant characteristics that may be used to characterize a Blockchain system’s scalability. These characteristics of Blockchain scalability are described and presented in Figure 3 .

Blockchain scalability aspect.

2.4. Scalability Trilemma in Blockchain

Although Blockchain has become more attractive in recent years, one of the most significant issues with Blockchain-based electronic voting systems is scalability, which might restrict its potential as a disruptive technology. As a result, this study aims to look into and evaluate existing initiatives to improve the scalability of Blockchain-based electronic voting systems [ 94 ]. As a result, we use a definition of scalability from recent research to describe scalability in electronic voting systems in the context of this study. The scalability trilemma might relate to decentralization, security, and scalability [ 95 ]. It is essential to remember that the trilemma is only a model for the different obstacles that Blockchain technology faces [ 96 ]. The rule says that three elements cannot be combined at the same time simultaneously. So far, however, many researchers worldwide have experimented with many ways to optimize decentralization, scalability, and security.

Understanding the underlying scalability trilemma at the foundation of Blockchain architecture is critical. Blockchains suffer from a trilemma, as postulated by [ 97 ] Vitalik Buterin (cofounder of Ethereum) and further investigated by Multicoin [ 98 ] (an investment company that invests in Blockchain startups and crypto-related businesses as a “theory-driven investment firm”). They can only accomplish two of the following three features simultaneously. A Blockchain can have, at most, two of these three properties:

Scalability: A high rate of transactions per second; decentralization: involvement of a vast number of individuals in the construction and certification of blocks;

Security: Increasing the cost of gaining control over the network.

Scalability is not a priority for proof of work (PoW), a decentralized system that allows anybody to participate in mining or maintain a node. The cost of energy/hardware required to create accumulated hash power provides a security [ 99 ]. Just a few organizations control the world’s hashing power due to the proliferation of specialized and expensive Bitcoin mining hardware known as ASICs (application-specific integrated circuits) [ 100 ].

Decentralization and security are more critical to Ethereum than scaling concerning the second-largest network by market capitalization. Currently, the consensus process (PoW) is identical to that of Bitcoin. Its future proof of stake (PoS) mechanism will be built so that anybody may participate in block generation, just as in Bitcoin [ 101 ]. Proof of stake might be better than Bitcoin’s proof of work because the user does not need to buy costly equipment to participate in building blocks [ 102 ]. Consequently, the network will become more decentralized as the distribution of block producers becomes more diverse.

This study looked at current scalable Blockchain-based electronic voting systems, such as those included in the most recent surveys on Blockchain scalability or scalable Blockchain-based electronic voting, as well as the fundamental scalability concepts present in contemporary literature. As a result, this section analyses and specifies significant characteristics that may be used to characterize a Blockchain system’s scalability. This research defines these as other dimensions of Blockchain scalability trilemma in Figure 4 .

Blockchain Implications.

2.4.1. Decentralization over Scalability

Why have Bitcoin and Ethereum prioritize decentralization? Rather than prioritizing scaling, according to some observers, if these networks are to become widely adopted, they must be able to compete with Visa-like throughput. No one wants to utilize programs that take days, hours, or even seconds to complete a single task [ 103 , 104 ]. The criticism of Blockchains is legitimate, but the core benefits that Blockchains provide are missed, such as censorship resistance. Our return to traditional database systems offers censorship resistance. However, it comes at the expense of the efficiency provided by legacy systems such as Amazon Web Services. We will use traditional database systems if Blockchain platforms do not offer this functionality.

2.4.2. Security over Scalability

The security of a Blockchain system is critical as a unique, promising technology aiming to build a name for itself by upgrading current infrastructure. Many crypto projects have prioritized decentralization and scalability above the security [ 105 ], with a slew of high-profile exchange breaches and manipulated source-code vulnerabilities. For all of its benefits, Blockchain ecosystems rely on the robustness of the underlying source code, which, like everything else, must be thoroughly scrutinized. Both decentralization and scalability will flourish if security is established; however, the decentralization process is ongoing, and scalability must be continually enhanced [ 106 ]. Blockchains have become an enticing target for hackers because the Blockchain source code is freely available to the public and has the potential for monetary benefit from a successful assault. While scalability concentrates on the positive aspects, security protects against the negative aspects, which are vital but often overlooked by [ 107 ]. Good Blockchain use cases have been inhibited by failures, such as the well-known decentralized autonomous organization (DAO) assault, which resulted from shoddy source-code security.

2.4.3. Scalability over Security and Decentralization

Scalability leads to the ability of Blockchain technology to handle large transaction flow and future growth. Scalable Blockchains will not suffer as use cases multiply and Blockchain technology becomes more widely used [ 108 ]. The word “scalability” is used to identify Blockchains that cannot handle an increase in demand. According to the Blockchain trilemma, it is possible to achieve higher scalability, but this would come at the expense of either decentralization, security, or both fields [ 109 ]. Traditional, centralized systems offer faster network settlement times and higher usability than Blockchain networks [ 110 ]. Many Blockchain systems have achieved decentralization and security; however, scaling is a significant problem for today’s most popular decentralized networks, as shown in Figure 5 .

Blockchain scalability trilemma.

Recently, there has been a growing interest in developing electronic voting systems via Blockchain technology. An overview of the most frequent answers found in the protocols, an introduction to current research in Blockchain technology, and an essential guide to the most prevalent challenges that the proposed solutions encounter are all possible outcomes of this article. The following is a list of the paper’s most important findings:

A comprehensive assessment of studies on scalable Blockchain-based electronic voting systems;

Identifying the most critical trends in the subject;

Identifying the key issues that scalable Blockchain-based electronic voting systems confront.

Between 2017 and 2022, this paper will research electronic voting systems based on scalable Blockchain technology. These databases IEEE Digital Library, Scopus, Springer Link, ACM, and Science Direct were searched to locate the papers used for the research.

3. Related Work

Blockchain technology has several uses in various industries, such as banking and finance, IoT and media, energy, health, logistics, and many more. In addition, new fields and ways of use are continually being investigated. The authors of [ 111 ] comprehensively evaluate several articles on Blockchain technology in information systems and give a comprehensive list of applications organized by Blockchain technology problems. This section provides a fundamental analysis of previous research that looked at scalable Blockchain technology for electronic voting. This research used digital libraries such as IEEE Xplore Digital Library, Scopus, ScienceDirect, SpringerLink, and ACM Digital Library to identify and review the existing literature to conduct a methodical study of such efforts. It allowed us to perform a rigorous study analysis of the efforts made. To identify existing surveys, this study focused on efforts to accomplish solutions for scalable Blockchain for electronic voting, as presented in Table 2 . This investigation revealed many potential options [ 112 , 113 , 114 ]. These are broad studies of Blockchain technology, and they mention scalability as a significant challenge for Blockchain. These examinations do not specifically investigate or address the scalability of Blockchain technology, and as a result, they have been excluded from the scope of the present study.

Research questions table.

Currently, research is being carried out on using Blockchain technology in online voting systems. The authors of [ 115 ] describe and compare numerous Blockchain-based electronic voting systems in their summary on voting. The deployment of Blockchain-based electronic voting systems [ 12 ] presents both threats and potential. Another significant survey was performed in [ 106 ], whose authors researched several Blockchain-based electronic voting systems to see how they adhere to existing international standards and conventions. To conclude, specific commercial Blockchain-based electronic voting systems are given and discussed in [ 116 ] in addition to an open electronic voting platform.

The authors of [ 117 ] investigated electronic voting obstacles and the present state of the Blockchain-based e-voting systems. According to [ 118 ], electronic voting may be unavoidable when comparing conventional voting with distant voting through the Internet. Finally, the authors of [ 119 ] present an overview of the current voting systems by describing several voting techniques, their benefits and drawbacks, and technical breakthroughs in the sector.

Numerous articles have been written on merging Blockchain technology with electronic voting systems. The results show how each method has distinct aims and is executed differently in these articles. These publications cover a variety of techniques to accomplish various objectives using a variety of ways. That is why we are performing an SLR on scalable Blockchain-based electronic voting to obtain a handle on what is new in the industry.

In conclusion, these studies lack both a systematic strategy for conducting the review and sufficient depth in current initiatives to address the scalability of Blockchain for electronic voting. Consequently, there are gaps in the coverage of several aspects of Blockchain scalability and the survey’s depth and breadth. Furthermore, due to the ever-increasing length of the Bitcoin chain and recent advancements such as Segregated Witness (SegWit), the scalability of Blockchain has recently garnered significant interest. Consequently, a current and extensive effort is necessary to systematically assess the scalability of Blockchain technology for electronic voting based on its present level of development. This evaluation aims to identify the work that has already been carried out, the existing limitations, and the potential avenues for future research. The first comprehensive literature assessment, based on [ 120 ], considers current initiatives that address all areas of Blockchain scalability in electronic voting systems by selected based on nine QAC discussed in Section 4.8 . Some of the selected and related work is mentioned in Section 5 with the related studies, along with the references, research methods used, and a summary of their results, as well as pointing out the research gaps.

4. Research Methodology

We used an SLR to answer the study questions, and we followed the guidelines presented in [ 120 ]. Iteratively moving through the phases of planning, carrying out, and reporting on the review was one of the strategies we sought to use to conduct an exhaustive analysis of the SLR. The following sections explain the systematic literature review approach and an overview of the scalable Blockchain electronic voting studies.

4.1. Systematic Literature Overview and Process

A systematic literature review, also known as an SLR, is a secondary research method that follows a predetermined plan to locate, examine, and evaluate published research associated with a specific topic, problem, or phenomenon [ 120 ]. There are five stages to the procedure:

Planning the review;

Selection process;

Conducting the review;

Screening and refinement;

Reporting the review.

Establishing research topics and defining a review strategy are the two goals of the review-planning phase. This step essentially presents the research’s scope. The primary goal of the review phase is to develop a search process, implement it, and analyse as many suitable primary papers as attainable. Following this phase, a collection of relevant articles will be picked from all of the available research papers. These papers may then be reviewed and used to answer the research questions. The last phase of the review is the reporting process, which entails composing the findings appropriately for presentation. This process ultimately produces the whole research report in a suitable format, which in this case, is a research paper. The steps of the systematic literature review are shown in Figure 6 , together with the artefacts acquired after each phase.

The process used to identify, gather, and refine research articles.

4.2. Research Questions

By examining existing scalable Blockchain-based voting systems, this article intends to shed light on the most prevalent trends in electronic voting. To attain this goal, the research topics listed in Table 2 will be addressed.

As per our research, we interpret what we found in the literature and check if it is feasible, riveting, novel, ethical, and relevant to this research. During our examination of the literature, we ensured that the questions we produced were sufficient to demonstrate their relevance and that the techniques of analysis used were suitable.

4.3. Selection of Primary Study

To highlight the importance of primary research, specific keywords were categorized into a journal or search engine search feature. The keywords were selected to facilitate the discovery of study results that would contribute to answering the research questions. Moreover, “AND” and “OR” were the only operators used to limit this research. The search strings were as mentioned in Table 3 .

Query strings table.

Different search terms have been used to obtain the data in this research. This way, we did not miss any vital articles because some authors used variants of words to differentiate their work from others. This research tries to obtain and filter all the required data for data gathering, as shown in Figure 7 . The platforms searched were:

ScienceDirect;

IEEE Xplore Digital Library;

SpringerLink;

ACM Digital Library.

Terms that form the search string.

The search platforms were conducted using the title, keywords, or abstract, relying on the search platforms or databases. On the 31 March 2022, we conducted the searches and analysed all of the research that had been published up to that time. These searches yielded filtered results using the inclusion/exclusion criteria described in Section 4.4 . The criteria enabled us to generate a collection of findings that we could then put via [ 121 ] snowballing process. Snowballing iterations continued until there were no more articles that fulfilled the inclusion criterion.

4.4. Inclusion and Exclusion Criteria

To filter the results of a database search, a set of inclusion criteria (IC) and exclusion criteria (EC) was developed in Table 4 and Table 5 include a comprehensive list. Studies that might be included in this SLR include case studies, uses of cutting-edge technology built on the Blockchain technology, and discussions on the progress of existing security processes via Blockchain integration. The included articles were peer-reviewed and published in the English language. Because Google Scholar may produce lower-quality reports, any results showing in Google Scholar were checked for compliance with these standards. This SLR has the most up-to-date findings from the research. The essential inclusion and exclusion criteria are listed in Table 2 .

Inclusion criteria for systematic literature review.

Exclusion criteria for systematic literature review.

4.5. Strategy for Search

The following online libraries and archives were combed for information: IEEE Digital Library, Springer Link, Scopus, ACM Digital Library, and Science Direct. The study questions were prepared using the PICOC (population, intervention, comparison, outcomes, and context) [ 122 ] criteria in the review protocol.

Population: Articles describing scalable Blockchain-based electronic voting solutions for big or small-scale elections were reviewed.

Intervention: Gathering information on electronic voting systems built on Blockchain platforms.

Comparison: The results of the research will not be compared.

Outcomes: It is essential to understand the scalability of Blockchain-based electronic voting systems and how they are utilized in real-world situations, advantages and disadvantages, and the cryptographic methods.

Setting: Electronic voting, scalable Blockchain electronic voting, and Blockchain.

With this in mind, the following search phrase was eventually generated for searching the selected databases after numerous iterative tests: (blockchain OR block-chain OR distributed ledger) AND (voting) AND (large-scale OR national level) AND (scalable OR scalability) AND (lightweight).

4.6. Data Extraction

The search string to query the databases yielded 201 papers: 20 from Scopus, 34 from IEEE Digital Library, 83 from Springer Link, 22 from Science Direct, and 42 from ACM ( Figure 8 ). This research was conducted by PRISMA (preferred reporting items for systematic reviews and meta-analyses). This process is shown in ( Figure 9 ). For Scopus, IEEE Digital Library, Springer Link, ACM, and Science Direct, those percentages equate to 10 percent, 17 percent, 41 percent, 11 percent, and 21 percent, respectively ( Figure 10 ). Figure 11 shows the graphical representation of publications obtained for each queried database per year. These papers went through a filtering process that was divided into four stages:

The initial investigation, during which the majority of the relevant texts were gathered.

Duplication removal, where removes the duplicate papers.

The final selection was based on the title and abstract, and the inclusion and exclusion criteria were applied to the results.

After a thorough reading, all chosen papers were subjected to inclusion and exclusion criteria.

In the first stage, 201 papers were produced, followed by 201 papers in the second stage, 101 papers in the third stage, and 76 papers in the fourth stage, as shown in Table 5 .

Number of papers obtained from each queried database.

PRISMA systematic literature review process diagram.

Percentage of articles found in each database searched.

Graph of publications obtained for each queried database per year.

4.7. Data Analysis

Following the selection method, a framework for data extraction and synthesis of data was established. Following its implementation, data were extracted and synthesized from the 76 articles. Table 6 shows the form as well as its contents.

Data extraction.

4.8. Quality Assessment Criteria

All studies shown in this paper were selected based on nine quality assessment criteria (QAC) presented in Table 7 . QAC are used to refine and analyse the collected data. The presented paper satisfied the criteria to check the quality of the data collected for this research.

Quality criteria.

4.9. Compilation of Results

There are several challenges to the research’s validity. To begin with, not all relevant sources may have been discovered. The search was carried out across many databases using the most general search query feasible to counteract this. Thus, a substantial amount of research should have been conducted. The search was also undertaken to avoid discrimination and ensure internal validity. The use of well-known databases and the complete exclusion of grey literature ensured that the study’s external validity was maintained. As previously indicated, the complete search query was performed to collect the most relevant information from database search engines.

When undertaking a systematic mapping study, there are numerous threats to consider. An exhaustive search for relevant research and information may be impossible. This study identified several search parameters and investigated multiple databases to eradicate this threat. Using several criteria and logical operators could expand the coverage. This study sought to find all relevant documents using various keyword combinations. Even though the topic is new, most of the research conducted following the exclusion measures was published in 2017–2022. As a result, the missing paper review on the subject has too little an impact on these conclusions. Unpublished or associated works not obtainable in the chosen scientific database pose a threat. The internal validity is unaffected by the removed publications because the databases are well-known. Although this research encircled the articles following the designation criteria, there may still be a margin of error owing to the original sample.

5. Result Presentation

The findings of the systematic literature review of the selected 76 papers are reported in this section. Table 8 lists the papers that were chosen. Each research question is explored in its subsection. On the other hand, the primary subsection gives the findings of the research’s quality assessment.

Papers about Blockchain for electronic voting selected for analysis.

5.1. Overview

Only studies from 2017 to 2022 were accepted for this study to observe the most recent research and ideas implemented in electronic voting based on scalable Blockchain technology. Table 8 shows the chosen article with benefits and years. All the selected articles were chosen based on the earlier criteria and then refined accordingly.

5.2. RQ1: What Are Some of the Most Well-Known Proposals/Implementations for Scalable Blockchain-Based Electronic Voting?

As previously said, there are a variety of Blockchain implementations. As a result, it is necessary to determine which one is currently investigated in electronic voting. Figure 12 shows which Blockchain implementations were found and how many times they were mentioned in the literature. Table 9 shows the relationship between specific articles and Blockchain framework implementations.

Implementation of Blockchain in electronic voting.

Studies utilizing specific Blockchain implementations.

The first is [ 123 ], in which the authors claim that the hybrid consensus model ensures integral scalability and security. In addition to this, the second study [ 124 ] focuses on the system usability scale (SUS) test, which measures the efficacy, efficiency, and community satisfaction with the Blockchain-based electronic voting system. However, the systems are inappropriate in terms of authentications. In the third paper [ 125 ], which was initiated to ensure security using Blockchain and trust computation, the proposed mechanism shows a better success rate in simulation, but the accuracy did not confirm. In the fourth article [ 126 ], the authors look at how a transaction malleability attack may be executed. Even though the studies revealed the importance of variables such as network latency and block creation rate, the suggested approach has been implemented on a permissioned Blockchain instead [ 128 ], which advocates using permissioned Blockchain technology such as Hyperledger Fabric.

Furthermore, the authors argue that cryptocurrencies are inappropriate for electronic voting. Bitcoin is very famous in the financial sector and not in services, but it cannot deny the importance of Blockchain due to its first application. Here are some of the authors using Bitcoin in their research, such as [ 7 , 24 , 128 , 128 , 149 , 150 , 156 , 164 ].

In the services sector, with 29 articles, Ethereum is the first most popular Blockchain system, as below [ 123 , 181 ]. Ethereum is a decentralized platform that is open-source and can be accessed anywhere globally (Ethereum Foundation, 2014). It operates on both a public and a private Blockchain architecture. Enabling smart contracts, also known as programmable contracts, can automatically carry out their terms between two parties. Because it is used in all studies, this feature is critical for choosing this Blockchain implementation. It is worth emphasizing that Ethereum is a proof-of-work system, with each transaction on the Blockchain costing gas. It suggests that any system based on this technology ought to take into account any expenses incurred as a result of using it. These systems may not be suitable for large-scale elections because of the possible costs or the added strain that comes with managing virtual currency. The Linux Foundation is the organization in charge of managing the Hyperledger commercial Blockchain project.

It is a worldwide corporation that provides the essential structure, rules, norms, and tools for developing open-source Blockchain and associated applications for usage in various sectors. It is meant to facilitate pluggable implementations of diverse components and handle the complexities and subtleties that exist throughout the economic ecosystem. The above authors [ 163 , 185 ] used Hyperledger Fabric for private Blockchain, although Fabric is much faster than the rest of the above Blockchain frameworks, but the network is not decentralized in any way. In the vast majority of cases, it is controlled either by a single entity or by a group that has shared responsibility. Two different motivations led to the decision to concentrate some portions of the database. First, it is managed by a group, and second, it is often hosted on a centralized cloud service provider such as Amazon Web Services or Microsoft Azure.

5.3. RQ2: Were Those Solutions Tested in a Real-World Scenario?

This question tries to answer if any of the 76 possible solutions explained in the 76 articles chosen were used in an actual election or referendum, whether the results impacted the final product, and how that impact would have been felt. Some of the scenarios were just tested and simulated to check the feasibility of the mentioned solutions. The above solutions have been implemented in some states, but not on a large scale or country level. Some small organizations implemented internal voting, and they found some flaws presented in these solutions and needed more research to obtain fully controlled and decentralized results.

5.4. RQ3: What Are the Verification Methods Used to Test Those Solutions?

This question aimed to find out what testing procedures were used to verify e-voting systems. Table 10 shows a list of the test techniques that have been identified, along with their publications. The analysis of assessment criteria is a test method designed for writers to officially and informally evaluate how well their proposed systems meet a set of requirements. It is a form of verification that is used in the majority of publications.

The methods of verification employed in the chosen articles.

Scalability testing is a type of testing through which the developers perform a formal and informal investigation of the provided solution’s capacity to manage many users and transactions simultaneously, such as those present during an election. One example of this testing scenario is when voters cast their ballots online.

Performance tests are a type of method test in which the authors verify the performance of their solution in the real world. It involves load testing and monitoring the time it takes to complete various election processes, such as voter registration, setup, and ballot casting and tallying.

Security analysis is a testing method through which authors formally and informally analyse and define the security qualities of their systems in response to specific attacks such as reply attacks, DDoS attacks, Sybil attacks, and man-in-the-middle attacks. Examples of these attacks include reply attacks, DDoS attacks, and Sybil attacks.

Cost evaluation is a testing approach in which writers assess the expenses associated with using their product. It is essential when the Blockchain platform is open to the public and employs a cryptocurrency such as Ethereum, where each action has a cost measured in gas [ 151 , 159 ] conducted three types of tests, while only [ 131 , 183 ] ran four types.

5.5. RQ4: What Are the Different Cryptographic Solutions Employed in Previous Research?

The goal of this topic was to find the more often utilized cryptographic solutions in present electronic voting research. Table 11 shows the results linking cryptographic solutions to specific research articles.

Explicitly revealed cryptographic solutions in researched articles.

The Advanced Encryption Standard (AES), also often referred to as Rijndael, is a standard for the encryption of electronic data established in 2001 by the National Institute of Standards and Technology in the United States. Around the globe, critical data stored in software and hardware are encrypted using AES. It is essential for the government’s data security, cybersecurity, and computer security [ 127 , 134 ].

Homomorphic encryption is a kind of cryptographic solution that enables the generation of ciphertext to perform computations that provide the same result as if those computations had been performed on the plaintext. This type of encryption is known as symmetric-key encryption. Homomorphic encryption is employed to encrypt votes as mentioned in these articles [ 128 , 179 ].

The Rivest–Shamir–Adleman (RSA) algorithm is an asymmetric encryption technique that encrypts and decrypts data using two independent keys known as public and private keys. When using RSA, sensitive information may be encrypted using a public key, and the encrypted message can only be decrypted using a private key [ 137 , 160 ].

Elliptic curve cryptography is a key-based encryption technique, sometimes known as ECC. The encryption and decryption of data sent over the Internet is the primary emphasis of the ECC protocol, which makes use of distinct public and private key pairs. Concerning ECC, the cryptographic technique known as Rivest–Shamir–Adleman (RSA) is often discussed [ 24 , 162 ].

The elliptic curve digital signature algorithm, often known as ECDSA, is a kind of digital signature algorithm (DSA) that generates signatures using elliptic curve cryptography keys (ECC). This equation is based on public-key cryptography, and it is quite effective (PKC) [ 129 , 131 ].

As can be seen, the cryptographic solutions that are utilized the most frequently include a variety of digital signatures (12 articles) for authentication and authorization, ElGamal (4 articles) for anonymity and privacy, and DSA encryption of various types (1 article) for operations on encrypted votes, such as counting. The SHA (secure hash algorithm) (14 articles) is an algorithm that is extensively used in security protocols and applications. Some examples of these include transport layer security (TLS), pretty good privacy (PGP), secure sockets layer (SSL), Internet protocol security (IPsec), and secure/multipurpose Internet mail extensions (S/MiME).

5.6. RQ5: Were the Cryptographic Operations Used in Prior Solutions too Costly and Time-Consuming?

The goal of this question was to find the cost and time of the current cryptographic solutions in the latest research regarding scalable electronic voting systems. Table 12 shows the results, linking cryptographic cost and time to specific research articles. The United States government protects sensitive information via encryption known as the Advanced Encryption Standard (AES), a symmetric block cipher. Encryption of sensitive data all over the globe is accomplished with the help of the AES algorithm, which is implemented in both software and hardware. It is essential for the preservation of data and the security of government computers and cybersecurity, [ 127 , 134 ]. AES focuses mainly on the four steps used in each round of AES encryption as follows: (1) byte substitution, (2) shift rows, (3) mix columns, and (4) add round key.

Cryptographic operations.

AES is at least six times quicker than triple-DES (Data Encryption Standard). A substitute for DES was required as its key size was too small. AES is a symmetric algorithm designed for private-key cryptography. It is faster than RSA but only works when both parties transmit a private key.

Homomorphic encryption techniques are a kind of encryption algorithm that permits users to conduct mathematical operations on encrypted data. It is a beneficial property with several applications [ 39 , 128 , 133 , 151 , 159 , 165 , 179 ]. Currently implemented completely homomorphic systems are several charges of magnitude slower than unencrypted data operations. Homomorphic malleability is one of the various theoretical issues. It indicates that homomorphically encrypted data can be converted to another type of encrypted data.

The Rivest–Shamir–Adleman or RSA algorithm is the cornerstone of a cryptosystem. A cryptosystem is a set of cryptographic algorithms for certain security services or goals. It enables public-key encryption, which is used extensively to protect sensitive data, particularly when such data are sent over an unsecured network [ 137 , 160 ]. Due to the massive number of calculations, RSA is somewhat slow and costly. It is still slow in contrast to symmetric encryption techniques.

Elliptic curve cryptography, sometimes known as ECC, is a method that encrypts data using a key. Pairs of public and private keys are emphasized heavily in ECC’s approach to the decryption and encryption of online traffic. The cryptographic technique known as Rivest–Shamir–Adleman (RSA) is often cited in connection with ECC. Elliptic curves provide the same level of protection against intrusion as conventional security methods (such as RSA), but they do so with fewer bits. Elliptic curve cryptography requires, among other things, a decrease in the size of the device, a reduction in the amount of power that is used, and an improvement in processing speed [ 24 , 162 ].

ECDSA is a kind of DSA that makes use of keys obtained from ECC. This equation, which is based on public-key cryptography, is beneficial due to its efficiency (PKC). ECC is used to produce keys, resulting in far more minor keys than the typical key generated by digital signature [ 129 , 181 ]. Some studies claim that ECDSA is more efficient than RSA when signing and decrypting, but that it is slower when verifying signatures and encrypting data. In comparison to other cryptographic systems, the ECDSA provides significant benefits. With smaller key sizes, it gives more security.

The Diffie–Hellman key exchange is the foundation for the ElGamal encryption system, an asymmetric key encryption strategy that uses public-key cryptography. Taher Elgamal first described it in 1985 [ 132 , 162 ]. It is harder to factor huge prime numbers in RSA than in ElGamal, which relies on discrete logarithm calculations. RSA has been demonstrated to be more efficient than ElGamal in encrypting data. In contrast, the ElGamal decryption procedure is far quicker than RSA’s.

The DSA has been designated the Federal Information Processing Standard for digital signatures. Using the modular exponentiation and the discrete logarithm issue both come from the subject area of mathematics. DSA is faster at decryption and signature, but RSA is better at encryption and verification. When dealing with performance concerns, it is good to consider where the problem is (i.e., whether it is the client- or server-based) and then decide based on the basic methodology [ 144 ].

SHA is an acronym for a secure hashing algorithm that is safe and reliable. Data and certificates are hashed using SHA, a newer version of MD5. This algorithm, known as a message digest, results in a 160-bit (20-byte) hash value known as a message digest. Sensitive data may be protected via hashing and encryption. On the other hand, passwords should seldom be encrypted but rather hashed. The hash algorithm can only be used in one specific way, and that is: (it is not feasible to “decrypt” a hash in order to recover the value of the plaintext that it was initially being encrypted from). It is a good idea to use hashing to verify passwords, whereas encryption is used to secure users’ data, and it can be decrypted [ 182 , 185 ].

5.7. RQ6: What Are the Latest Blockchain Applications Focused on Scalability?

The selected articles can be categorized into three groups, as shown in Table 13 : the first is the small-scale or organization voting group, which consists of 20 articles including [ 183 , 185 ] that propose solutions and methods for small-scale voting, such as boardroom voting, etc. National voting is the second group, which consists of 24 papers [ 123 , 167 ] that describe e-voting on a large scale such as national elections, but these solutions are not tested in real-world scenarios; some of the solutions are verified formally and some of the solutions are tested by performing simulations. The third group comprises 18 publications [ 135 , 161 ] that provide solutions for generic voting. This category contains papers that did not specify the sort of election.

Scalability scenario classification.

5.8. RQ7: What Parameters Test the Performance and Scalability of the Electoral Process on a Large Scale?

Table 14 shows the parameters that have been identified to check the performance, highlighted in bold. Increases in block frequency may improve performance [ 140 , 178 ], while block propagation time sets a lower limit. The related work contradicts itself considering the effect of block size on performance, while [ 24 , 185 ] claims a favorable effect of increasing block size on performance. Depending on their instructions and storage access, different smart contracts may have various runtimes in terms of workload [ 2 , 48 , 134 , 136 , 141 , 142 , 143 , 144 , 146 , 147 , 151 , 156 , 157 , 159 , 162 ], Furthermore, [ 153 , 165 , 168 , 171 , 177 ], for example, reports a performance disparity. Node configuration and CPU usage are the parameters that describe a node’s computing power; they comprise hardware settings such as the quantity and kind of CPU and RAM. Only a tiny amount of research was conducted on this parameter in [ 14 , 34 , 179 ]. The impacts of network size are discussed in only a few studies [ 181 , 186 ].

Identified performance parameters.

Network structure/network usage is a parameter that describes the structure of the Blockchain network. This research is found in some of the work conducted in these papers [ 125 , 182 ]. Workload quantity is the number of transactions processed within a given time. Regarding workload quantity, the related work provides contradictory statements, such as in [ 1 , 165 ], while the quantity of miners/sealers/memory usage refers to actively participating nodes to be handled within the given time. Some of the work conducted on these papers was discovered during this investigation [ 14 , 164 ]. Blockchain client and API are referred to, as it is a user interface that connects to a Blockchain node or client network directly or via another service. During the initial investigation, some of the work on these documents was discovered clearly in these papers [ 136 , 166 ].

Subsequently, after applying the refinements to determine scalability parameters, 51 articles were picked to be retained in our study spanning three subcategories as follows. The first subcategory, throughput, includes 15 publications ( Table 15 ) that look at scalability issues. A fundamental component of scalability is transaction throughput, and almost all studies use the term “transactions per second” to describe throughput (TPS). It is the speed at which valid transactions are committed and added to the block when the stakeholders in a Blockchain network (miners) agree on how the network should function. It is worth noting that only these authors discuss the throughput [ 123 , 178 ].

Identified scalability parameters.

Meanwhile, the rest focuses on the second subcategory of scalability latency. In computer science, the term “latency” refers to the time that elapses between an input and an output. In Blockchain technology, having a low network latency is essential. Latency can discuss two types of delays in Blockchain: network latency and transaction latency. The network latency occurs between when a transaction request is initiated and when the network confirms the transaction. A transaction’s latency is a statistic of consensus efficiency that affects the processing and execution of large numbers of transactions. The second subcategory consists of 17 publications providing solutions for scaling the Blockchain by improving latency, such as [ 126 , 163 ]. In the following 19 articles [ 147 , 177 ], when modifying a parameter, these articles utilize throughput and latency instead of changes in throughput and latency (e.g., the network size or the hardware configuration of a node).

5.9. RQ8: What Are the Prior Approaches for Blockchain Scalability to Efficiently Enhance the Electoral Process on a Large Scale?

The goal of this question was to highlight approaches for Blockchain scalability to efficiently enhance the electoral process on a large scale. Table 16 presents a list of identified methods with their publications. On-chain methods boost the scalability of Blockchain by altering internal settings to reduce network latency and optimize the number of transactions and messages, respectively.

Prior approaches to enhance electoral process.

On-chain solutions include: Blockchain pipelining—an on-chain approach that adds blocks to the main chain without other nodes’ validation. It improves the transaction throughput of the Blockchain. The final decision on the block’s validity for forming the main chain is made through voting among nodes as a separate layer [ 145 , 187 ]. Blockchain delivery network—this research investigates solutions [ 126 , 164 ] that use cut-through routing-enabled gateways or cloud delivery networks. These ideas try to improve the transaction throughput or storage scalability without disrupting the Blockchain’s decentralized character. Block size adjustment—adjusting block size is another scalable method. These procedures are application-specific and require adjustment. Too many increases in block size can enhance the transactions per block, but latency is propagated. On the other hand, too much of a reduction in block size can raise block generation rate (BGR), improve latency, and cause frequent forks [ 1 , 188 ].

Off-chain solutions: Off-chain solutions carry out transactions outside the primary Blockchain network, reducing the required effort. These solutions are powered by Blockchain technology. Off-chain technologies such as payment channels link (LN), Raiden Network Token (RDN), or sharding may increase a Blockchain network’s horizontal and vertical scalability. These solutions have the potential to provide Blockchain-based solutions for devices with limited resources, such as Internet-of-things devices.

Payment channel networks: By constructing a micropayment channel, the payment channel allows several parties to conduct various off-chain transactions without publicly committing all transactions. Minimizing the workload on the main chain leads to an increase in throughput. In a typical payment channel network, just two transactions are required to update a record on the main-chain to complete all transactions between parties or satisfy the need for an on-chain transaction. Participants in this network can undertake an unlimited number of transactions. Through intermediaries, even parties not in a direct relationship can enter into transactions [ 128 , 160 ].

Sharding: A Blockchain’s mining node stores all the states, including account balance and transaction history, which reduces transaction throughput linearly. Sharding divides an extensive database into manageable pieces to boost efficiency [ 123 , 127 ]. In the Blockchain, it is the horizontal separation of the main chain into shards. Each partition/shard stores its state. Sharding is a technique that separates the main chain into multiple independent groups, even though it is considered an off-chain solution. As a result, each transaction broadcast on the network does not have to be mined by a single node. Each shard acts as its Blockchain inside the network through the Merkle tree and may be joined to the main chain using cryptographic means.

Hardware-assisted approaches: In addition to software-based approaches, the body of published research includes several solutions that employ specialized, trusted hardware devices for one of two purposes: either improving consensus or speeding up the transaction process to improve Blockchain scalability [ 129 , 146 ]. The hardware has high processing machines and trusted execution environments (TEEs), which enable efficient transaction management while maintaining both correctness and speed.

Parallel mining or processing: The conventional implementation of Blockchain technology is based on decentralized mining. Additionally, transaction throughput and scalability are severely limited in this implementation. The parallel mining methods improve the scalability of Blockchain networks by mining several blocks concurrently without making any fundamental changes to the Blockchain’s underlying structure [ 147 , 187 ].

Redesigning Blockchain: Through this research, the study discovered a few ways to devise an effective strategy, such as to design a new consensus structure, to deal with numerous properties of scalability such as increasing throughput and reducing latency etc. [ 152 , 185 ]. Although Graphchain and HashGraph leverage the nonlinear creation of blocks through the usage of directed acyclic graphs (DAG), certain techniques present as an alternate (other than Blockchain) scalable distributed ledger (DLT) solution. However, these methods are out of the scope of the current research.

6. Analysis and Discussion

According to researchers, electronic voting systems are expected to benefit from the use of Blockchain technology. The immutability of data and the system’s distributed nature are the primary benefits. Researchers have paid close attention to the issue of Blockchain’s scalability since it has emerged as a significant concern. We need ways and processes to increase horizontal and vertical scalability due to the growing usage of Blockchain technology in financial and nonfinancial industries. When scaling a Blockchain for large or countrywide elections, the most important pinpoints to consider are simplified storage, increased throughput, and reduced latency. Decentralized, secure, and scalable (DSS) Blockchain applications or solutions have been presented in various ways, each with its advantages and disadvantages. Blockchain cannot achieve its full potential unless the scalability issues are addressed. As a result, we have identified gaps in the current state of the art that will necessitate more work from the scientific community. In order to build scalable Blockchain, we have outlined the fundamental research problems below.

6.1. Sharding

Sharding is a method that may be used to increase the scalability of Blockchain. Graphchain [ 189 ] and Omniledger [ 190 ] are two examples of sharding-based techniques suggested to achieve low-level latency and high-throughput in a distributed database. Both of these techniques were developed in 2018. There are many other ways to solve such problems, but Graphchain has emerged as the most efficient and secure one [ 191 ]. However, these methods only apply to cryptocurrencies that do not require permissions. On the other hand, some other approaches were extended to all workloads but depended only on trusted hardware to reduce communication overhead [ 192 ].

In particular, message complexity reduction is the aspect of sharding and Blockchain sharding, which needs further investigation. Blockchain’s scalability depends on low communication costs per transaction (CCPT) [ 193 ]. CCPT is regarded as scalable in the context of Blockchain, either relying on hardware specifically designed for the purpose or trusting that all nodes are interested and would act rationally to sacrifice reliability to gain CCPT. Implementing decentralized reputation-management systems and load-balancing mechanisms that include an attractive incentive strategy are potential areas of investigation that could be pursued to prevent anomalous behaviour from nodes that do not have dedicated hardware [ 194 ]. Both of these areas could be explored further. Both of these areas are intended to prevent anomalous behaviour from occurring.

6.2. Consensus Algorithm

Due to the decentralized nature of Blockchain, the consensus algorithm is an essential part of every software stack. Even though Bitcoin is built on proof of work, various additional consensus algorithms have been suggested, comprising proof of stake, proof of authority, proof of weight, etc. An empirical investigation of consensus algorithms is necessary to understand and emphasize the applicability for various application domains [ 195 ]. This consensus algorithm may be a new topic of study that needs additional investigation by the scientific community.

6.3. Block Size Increase

As a result of the study, this research can identify the function block size and generation have in scaling Blockchain. Increasing the maximum block size is known as the block size increase. The blocks in Blockchain networks are created regularly, including a record of all transactions. Because the number of transactions that may be stored in a block is limited by the block size, raising the block size will boost throughput [ 196 ]. It can cause unacceptable propagation delays for blocks if the transmission delays caused by larger blocks are too significant. However, most of these attempts have focused on the Bitcoin Blockchain and are consequently limited to the Bitcoin settings. Such an examination should be carried out on a more abstract platform such as Ethereum or Multichain to emphasize the benefits and weaknesses, especially scalability. It is hoped that this will help developers understand the importance of Blockchain parameters and enable them to select appropriate Blockchain platforms for various application areas.

6.4. Directed Acyclic Graph

Another Blockchain form distinct from regular Blockchain is the decentralized autonomous group or DAG. It is a network consisting of separate transactions connected to several other individual transactions [ 197 ]. The DAG is a tree that grows from one transaction to another, branching out from one transaction to another, etc. Blockchain is a connected list of blocks.

6.5. Increase Authorized Hardware Devices to Decrease Block Generation Rate

Using innovative or approved hardware equipment for mining and verification on a permissioned (consortium) Blockchain may slow the pace at which blocks are generated, directly influencing the amount of business conducted on the network [ 198 ]. On the other hand, the use of this technology in permissionless (public) Blockchain systems requires an effective incentive mechanism to persuade miners to employ full gear with increased processing power, storage space, and memory.

7. Conclusions

The main aim of this paper is to review and analyse the current research on scalable voting systems, primarily based on Blockchain technology. Nevertheless, developing and implementing an electronic voting system is not a simple undertaking. Electronic voting systems must solve many problems, such as authentication, privacy, data integrity, transparency, and verifiability. This report is a systematic mapping study that summarizes the current research on scaling Blockchain technology for electronic voting. One of the fundamental issues that prevent the general use of Blockchain technology in various application fields, including electronic voting, is the impossibility of scaling Blockchain to accommodate increasing numbers of users. Recent occurrences, such as the epidemic that has spread all over the globe and the rise in the number of instances of election fraud, have resulted in the need for a voting information system that is effective, scalable, safe, and dependable. Because of this, investigations into new and improved Blockchain-based solutions are still being carried out. The primary objective of this research is to shed light on the various Blockchain-based voting options currently available. The paper presented the first systematic effort to identify and collate existing efforts related to Blockchain scalability in these aspects. It includes leveraging Blockchain to achieve scalable applications, mechanisms, and methods to enhance Blockchain scalability by contributing to the core Blockchain functions and efforts to define the scalability challenges through analysis of Blockchain-based electronic voting solutions. Several study holes in the field of elevating have been provided that need to be considered for further investigations. There may be other downsides, such as resistance to compulsion, scalability assaults, reduced transparency, and untrustworthy systems, all of which need to be overcome. Testing the electronic voting system may be conducted in various ways, much like trying any software, including acceptability, performance, and security. On the other hand, there is no universally accepted method for checking and ensuring such systems’ accuracy or reference data. At the very least, no one is referenced in any considered books. In addition, there is no indication that these technologies are being utilized in reality, making it hard to conduct an exhaustive study. Most of the chosen papers provide verifiable answers, one of the primary challenges of the electronic voting method. Other concerns often addressed include protecting the confidentiality of ballots and determining who is eligible to vote. On the other hand, many solutions have drawbacks such as a deficiency in coercion resistance and receipt freeness, expenses associated with functioning on a public Blockchain, and susceptibility to certain types of assaults.

Author Contributions

U.J.: writing, original draft, investigation and editing. M.J.A.A.: conceptualization, methodology, supervision. Z.S.: conceptualization, methodology, supervision. H.A.H.: writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Funding Statement

We would like to thank the Universiti Kebangsaan Malaysia for funding. Code PP-FTSM-2021.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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