Are franchisees more prone to employment standards violations than other businesses? Evidence from Ontario,Canada

Abstract

Using an administrative dataset from the Ontario Ministry of Labour, we investigate three hypotheses about employment standards violations among franchised businesses: (1) franchisees have a higher probability of violating employment standards than other businesses, (2) franchisees have a higher probability of monetary/wage-related ES violations than other businesses, and (3) franchisees have a lower probability of repaying monetary/wage-related violations than other businesses. The results of our statistical models suggest that overall, franchisees are indeed more likely to violate ES, have a higher probability of monetary/wage-related violations, and are less likely to repay such violations. However, the results vary substantially by industry. While franchisees had only marginally higher probabilities of an ES violation in two of the seven industry-groups examined, five of the seven industries showed substantially higher probabilities of a monetary violation. The results also show that franchisees in three industry groups (retail, accommodation and food services, and education, public administration, healthcare and social services) are particularly prone to monetary violations.

JEL codes: J83, J88, J89

Keywords

Canada compliance employment standards enforcement franchising industry labour standards legal violations Ontario

Introduction

Franchised business models are often conceptualised as beneficial to an economy because they reputedly encourage entrepreneurship, the efficient provision of goods and services, and invigoration of local job markets (e.g. Grünhagen and Witte, 2005; Hunt, 1972; Michael, 2014; Sanghavi, 1998; Watson, 1997; Welsh et al., 2006). But franchising also represents a prevalent form of workplace fissuring, whereby franchisors can legally evade many of the costs and responsibilities of having direct employees. Franchised workplaces, like other fissured environments, may have limited employment standards (ES) enforcement, and promote precarious jobs that can leave workers vulnerable to mistreatment. Compared to other types of fissuring, franchising exerts particularly strong pressure on business owners to extract profits from labour costs; consequently, franchisees may experience greater compulsion than other types of businesses to violate legal minimum ES in their respective jurisdictions (see Weil, 2014). In this paper, we examine empirically whether franchisees have a higher propensity for ES violations than other businesses.

Franchising is a prominent business model that occurs in many industries. Conservative estimates suggest that as of 2018, franchising contributed over USD1.75 trillion, or 2.7% to annual global gross domestic product (GDP).¹ Franchised businesses are estimated to employ more than 21 million people across 3 million locations, and in over 40,000 brands (Hoy, 2017). But for many workers in franchised businesses, jobs are precarious, or concentrated in industries with high rates of precarious employment (Bennett, 1994; Weil, 2009, 2011).

Franchising plays an important role in the Canadian and global economies. Currently ranked as the world’s second largest franchising sector, franchising accounts for about 10% of Canada’s GDP, and employs 1 in every 10 people engaged in paid work in Canada (US International Trade Administration, 2016: 15; Canadian Franchising Association, 2018a). The number of new franchise brands in Canada also grew 20% between 2013 and 2017 (Canadian Franchising Association, 2018a, 2019). It is no surprise then, that in a 2016 trade report, the US International Trade Administration (US Department of Commerce, 2016) ranked Canada as one of the most promising markets in the world for US-owned franchisors. US-based brands have a strong presence in the Canadian market. Among the top 100 franchise brands in Canada by number of locations, 53% are internationally based, and 49% come from the US (US Department of Commerce, 2018: 11).

As Weil (2014) illustrates, franchising is highly competitive, making the strict maintenance of brand standards vital to the continued success of the franchise. However, labour standards pertaining to franchisees’ employees are generally not included in these arrangements. Consequently, the pressure to find efficiencies within the constraints of extensive operating standards leave franchisees with few avenues for protecting profits outside of skirting wages and labour standards. Weil’s research suggests that these behaviours are endemic to the highly competitive environment of franchising.

Franchising’s large footprint in Canada means that this business model may expose a disproportionately high number of workers in the country to potential mistreatment. As well, the abundance of US-based brands in Canada arguably intensifies pressure on the country’s franchisees to find efficiencies, given that US-based brands are among the world’s most efficient due to being time-tested in such a hypercompetitive market (Michael, 2014).

In this article, we model the probability of ES violations among franchised businesses in the province of Ontario. Ontario is Canada’s most populous province with about 40% of the country’s 37 million inhabitants, and it accounts for the largest share of the national workforce.² As the most economically diversified province, Ontario also provides a comprehensive picture of ES violations across a full range of industries and workplaces. Most importantly, Ontario dominates when it comes to Canada’s franchising sector. Fifty-six percent of the estimated 1400 franchise brands operating in Canada are headquartered in the province, and it is the location for 65% of the country’s 75,000 franchise outlets.³ Ontario also leads the country in various measures of its franchising sector’s contribution to the national economy.⁴

We begin with a brief review of the literature relevant to ES compliance in franchising. The subsequent sections present, respectively, the data and methods, and an analysis and discussion of the findings. In the conclusion, we suggest avenues for future research, and propose strategies for redressing ES violations in franchising.

Literature

Franchising models were first developed by US entrepreneurs in the mid-1800s to stimulate business expansion. Since that time, franchising has become a worldwide phenomenon (Blair and Lafontaine, 2005). While debate continues over an absolute definition of franchising (see Frazer and Grace, 2017; in Hoy, 2017), we adopt Curran and Stanworth’s (1983) popular working definition, defining franchising as a business model in which one entity (the franchisor) enters into a contract with another entity (the franchisee) who is independently financed to operate under the franchisor’s trade name as an owner-manager providing a good or service using a market-tested format specified by the franchisor. As a condition of using the franchisor’s format or model, franchisees also typically pay royalties and/or an upfront fee (Stanworth and Curran, 1999: 326). Since there is little substantive difference among the various types of franchising (Blair and Lafontaine, 2005), we use this definition with reference to all its forms.

Research on franchising has been most prominent in the fields of management, economics, marketing, law, and entrepreneurship. Within these fields, the central concern has been the growth and efficiency of franchising as it relates to organisational form, legal contracts, supply chain management, the impact of technology, or how parties in franchising navigate challenges and cultivate opportunities (see Combs et al., 2011; Dant and Kaufmann, 1999a, 1999b; Fried and Elango, 1997; Hoy and Shane, 1998; Lafontaine, 2014; Shane and Hoy, 1996). More recently, these fields have also paid increasing attention to franchising in emerging markets, and in social entrepreneurship (see Hoy, 2017). While informative, this literature focuses primarily on issues in franchising that pertain to the creation of wealth for enterprises and their owners. Less considered is how franchising systems influence wages and working conditions for those directly employed by franchisees, and thereby local labour markets.

Bennett’s (1994) analysis of Australian labour law provides one of the earliest critiques of franchising’s effect on ES. By underscoring franchising’s reliance on hiring strategies and organisational designs that tend to stifle employee voice, Bennett highlights its potential as a tool that can be used to evade legal and social responsibilities to employees. While the industries in which franchising are prominent already tend to have high rates of precarious employment (e.g. retail, food, and accommodation), Bennett (1994: 171–181) provides some of the earliest empirical examples of how problems with wages and working conditions in these types of industries have risen concomitantly with franchising.

Franchising and ES violations

As reiterated throughout Weil’s work on fissuring, the risk of ES violations should be higher in the franchising sector because this business model places great pressure on franchisees to be profitable by lowering their labour costs. This is due largely to the asymmetric terms of franchising agreements that strongly incentivise franchisees to put the lead firm’s profitability first.⁵ At the same time, such agreements typically stipulate that except for matters concerning the franchisee’s workforce, the lead firm retains control over all aspects of the franchisee’s operations. The result is a set of countervailing pressures that can encourage franchisees to extract profits from their workforce in illegal ways (Weil, 2009, 2011, 2014).

A workforce vulnerable to weak enforcement

Recent analyses of US franchising agreements strongly suggest that the constraints placed on franchisees by lead firms precludes many alternate profit-making strategies other than by extracting effort from a precarious workforce (Callaci, 2018, 2019) While not illegal, limited access to union protection makes such employees extremely vulnerable to the actions of franchisees already facing pressure to extract profits through minimising labour costs (Bennett, 1994; Weil, 2009, 2011, 2014). Under these circumstances, franchisees may be especially pressed to overlook the minimum legal entitlements of employees on matters such as wages, public holidays, overtime or vacation pay, rest and eating periods, limits on working time, or unauthorised payroll deductions.

Canadian data on the characteristics of franchisee employees are scarce. However, based on Callaci (2019), and on the demographics of the precariously employed in industries where franchising is prevalent, many are likely to be female, young workers, racialised or recent immigrants, or have low levels of education (Lewchuk, 2017; Noack and Vosko, 2011; Vosko 2020). Several major franchised brands also recruit employees through Canada’s Temporary Foreign Worker Programme (Polanco and Zell, 2017: 270).

More generally, a weak ES enforcement regime further undermines the incentive to comply with minimum standards because businesses may deem that the benefits of violating outweigh the risks of being caught. For example, in countries such as the US, Canada, and Australia, a waning commitment towards effective deterrents, consistently applied penalties, and adequate Employment Standards Officer (ESO) staffing may actually embolden employers to disregard minimum labour standards (e.g. see Bernhardt et al., 2009; Clibborn and Wright, 2018; Maconachie and Goodwin, 2010; Vosko, 2020; Vosko et al., 2017; Weil, 2014). Direct evidence on how a weak ES enforcement regime specifically influences franchisees to violate minimum labour standards is lacking. However, all else being equal, the structure of these entities puts them under more pressure to commit such violations. Therefore, in theory, a weak enforcement regime may facilitate this behaviour by making the benefits of violating ES, relative to the risks of being caught, even more advantageous for this group.

No shared liability

Also facilitating minimum standards violations in franchising is the reluctance of many regulatory regimes to find that franchisors share any liability for the transgressions of their franchisees (Davidov, 2015; Elmore, 2018; Griffith, 2019; Hardy, 2018, 2019; Ruckelshaus et al., 2014; Sanjukta, 2019; Steinbaum, 2019). Franchisors thus have no compelling economic reason to be concerned with whether their outlets are compliant with local labour standards.

Furthermore, the reluctance of lead firms to step in voluntarily, that is, in the absence of any legal requirement to do so, effectively condones their franchisees’ non-compliance with local labour regulations. In short, the lack of stronger internal incentives for franchisees to be compliant, combined with a weak ES enforcement regime, enables a culture where franchisees may be more inclined than other businesses to disregard labour standards.

Franchising and monetary violations

In franchised businesses, there is a fundamental tension between the motivation of the agent/franchisee and that of the principal/franchisor (see Lafontaine, 2005 on the agency problem in franchising). Since franchised workplaces are independently owned, tend to face more competitive conditions, and have relatively narrow profit margins, they are likely to have a lower stake in the brand’s reputation than their corporate-owned counterparts. As such, franchisee-owned locations would be more prone to evading standards to protect their profits while ‘free riding’ on the benefits that come with the brand’s reputation.

Researchers have examined this premise by comparing the risk of standards non-compliance between franchised, and corporate-owned locations on health-code violations (Jin and Leslie, 2009), on alcohol sales to minors (Utgård et al., 2015), and on back-wages owed (Ji and Weil, 2015). This research, though sparse, has found that franchised locations are at a higher risk of violating the standards under investigation than non-franchised locations of the same brand. Ji and Weil’s (2015) study is particularly relevant in that it empirically links franchising to the violation of wage regulations.

From the franchisor’s perspective however, ES non-compliance is not necessarily an agency problem. As Kellner et al.’s (2016) ‘diverse accountabilities’ model explains, franchisors employ a mix of management systems catering to this business model’s tiered structure of accountabilities. Where the customer is concerned, franchisors exhibit well-developed HR initiatives consistent with large organisations because brand reputation is at stake. However, with only franchisees legally accountable to employees, franchise outlets are more characteristic of small businesses. Franchisees are thus largely left to their own devices when it comes to HR involvement in ES compliance. Franchisors ultimately benefit from this dichotomous management approach. They realise economic rents through downloading the costs and risks of ES (non)-compliance, while further maximising profit through assuring the market expansion of a consistent product (Kellner et al., 2016).

In theory, violations of wage-related (or monetary) ES, such as unauthorised deductions, the failure to pay wages, overtime, holiday, or vacation pay, represent the most direct ways an employer illegally extracts profits from labour. This contrasts with violations carrying more indirect labour costs, such as failing to keep accurate records, issue wage statements, or provide entitled rest periods. Therefore, to the extent that franchising incentivises businesses to extract profits through the illegal skirting of labour costs, this should be reflected in franchisees having a relatively higher probability of monetary violations than other types of businesses.

There are numerous examples of franchisees’ direct labour costs being targeted through the broad wording of franchise agreements. In all such cases, lead firms use this discretion to impose financially opportunistic conditions under the guise of operational standards. For example, content analyses of franchising agreements in the US have found detailed conditions on all aspects of operations except wage rates (Elmore, 2016). To discourage certain types of competitive behaviours, no-employee-poaching clauses from the same brand are also common, especially among businesses where there is high turnover (Krueger and Ashenfelter, 2018). Such practices mean that franchisees often shoulder additional wage and training costs that need to be recouped through some other means. Another example is the case of franchisees from a large international fast-food brand, who are required to pay wages using payroll reports generated by the lead firm that were knowingly flawed (Elmore, 2016). Agreements that incentivise wage violations through granting franchisors direct control over a franchisee’s revenues and profits are another concern. Weil (2014) demonstrates this in a major US janitorial services brand that uses a highly centralised fee and remittance system.

Repayment of wages owing after a violation is detected

The same incentives that encourage monetary violations among franchisees may also lower a franchisee’s probability of repaying the amount owed when an ES violation is detected. As previously discussed, franchisees may be more likely to have wage-related violations because the architecture of franchising produces thinner profit margins. Therefore, any restitution demanded by labour inspectorates is the metaphorical equivalent of drawing water from a dry well. The other impediment is the historically limited political and economic capacity of most jurisdictions to recover monies owed, effectively undermining any disincentive effect that was intended in ES legislation and enforcement (see Vosko, 2020: Chapter 4). Collectively, these factors suggest that franchisees would have both less means and less incentive to repay monies owed when caught.

In this empirical analysis, we therefore test the following three hypotheses:

H1: Franchisees have a higher probability of violating employment standards than other businesses.

H2: Franchisees have a higher probability of monetary/wage-related ES violations (as opposed to non-monetary ES violations) than other businesses.

H3: Franchisees have a lower probability of repaying monetary/wage-related violations than other businesses.

The section that follows introduces the empirical data used to test these hypotheses.

Data

To examine the incidence of violations in workplace inspections, we draw on the Ontario Ministry of Labour’s (MOL) Employment Standards Information System (ESIS), an administrative database that is not publicly available.⁶ Since ESIS was not originally designed for research purposes, it has not undergone the same quality control and data verification process as survey data from large statistical agencies. However, it provides a complete record of workplace inspections conducted under the Province of Ontario’s Employment Standards Act (ESA), the legislation prescribing minimum labour standards for many of the province’s workers, and thus provides key insights into ES enforcement unavailable from any other source. We focus on 13,897 workplace inspections conducted from 2012/2013 to 2017/2018, the most recent fiscal year with complete data.⁷

We conceptualise the focal independent variable (business type) in two categories: franchisees (defined earlier), and all other business types. The latter category refers to any business that does not operate as part of a franchise network. While we distinguish between businesses that represent franchised brands and those that do not, we were unable to consistently differentiate corporate-owned from franchised locations among the franchised brands in ESIS. Therefore, our key independent variable may also contain an unknown number of corporate-owned locations. As previously noted, past research has found that corporate-owned locations of franchised brands tend to be more compliant with regulatory standards. Therefore, the presence of corporate-owned locations in our current measure of franchisees actually raises the standard of evidence required to support the hypotheses.

There is only a very low risk that these findings are biased by employees or dependent contractors who are misclassified as franchisees (see Weil, 2014). While this practice is well-documented in the janitorial industry (see Weil, 2014: Chapter 6), franchised brands in this industry comprise less than 1% of inspections in the ESIS data. Second, ESIS data only include businesses that have paid employees. Consequently, the cases of franchisee misclassification most likely to bias our results – businesses with no employees – are not included in the data.

Workplace inspections and ES violations

Outside of a limited number of federally regulated industries, ES in Canada are legislated provincially. In Ontario, this legislation is known as the ESA. This Act, which applies principally to employees not covered by a collective agreement (Vosko et al., 2016b), outlines minimum standards for workers on matters such as wages, overtime, and termination pay, working time, rest periods, and vacation entitlements. The Act also delineates the various administrative responsibilities of employers. Potential violations of Ontario’s ESA are identified by the MOL in two main ways: employees may submit a complaint about their employer which is subsequently investigated, or ESOs may carry out workplace inspections. This analysis focuses solely on ES violations detected via workplace inspections.

In the context of Ontario’s ES enforcement regime, workplace inspections are considered a proactive enforcement strategy because they are intended to deter employers from violating in the first place. They can also detect offences that may otherwise go unreported. Inspections are of three main types: regular inspections, consisting of visits to randomly selected workplaces; expanded investigations, which are launched when an ESO detects a violation from a complaint during the course of an inspection, and believes that more employees are affected; and targeted or blitz inspections, prompted by the MOLs focus on a sector where it suspects a high incidence of ES violations. The MOL’s Administrative Manual for Employment Standards (AMES) specifies that full workplace inspections focus on enforcing 11 core standards deemed to be of ‘collective’ interest within a workplace:

Public holidays;

Poster requirements;

Record-keeping;

Hours of work;

Eating periods;

Wage statements;

Overtime pay;

Unauthorised deductions from wages;

Minimum wage;

Vacation pay;

Temporary help agencies charging employees fees and providing information.

According to the ESA sections associated with each of these core standards in the ESIS violation record, the first six standards are generally treated as non-monetary violations, and the remaining five standards are treated as monetary violations. Following Casey et al. (2018), we adopt these same five standards in our measure of such violations. While some of the other standards may also be indicative of monetary violations in some circumstances (e.g. record-keeping), there is a direct link between monetary non-payment and the latter five standards.

Prevalence of ES violations by workplace type

Table 1 shows the incidence of monetary and non-monetary violations recorded in Ontario for the six fiscal years from 2012/2013 to 2017/2018.

Table 1.

Prevalence of violations in workplace inspections, by fiscal year.

	2012/2013	2013/2014	2014/2015	2015/2016	2016/2017	2017/2018	Total
Total number of inspections	2348	1902	1749	2630	2477	2791	13,897
Number of inspections with a violation	1676	1300	994	1703	1781	1626	9080
% of inspections with a violation	71.4%	68.3%	56.8%	64.8%	71.9%	58.3%	65.3%
% of inspections with more than 1 violation	54.3%	52.9%	39.7%	49.0%	51.4%	32.8%	46.4%
Number of inspections with monetary violations	972	785	548	1026	971	797	5099
% of inspections with a monetary violation	41.4%	41.3%	31.3%	39.0%	39.2%	28.6%	36.7%
% of inspections with more than 1 monetary violation	2.8%	3.1%	2.0%	2.7%	3.2%	2.4%	2.7%
Mean entitlement amount per inspection (CAD)	2929	3889	3455	4464	5033	4448	4080
Median entitlement amount per inspection (CAD)	762	742	732	912	897	955	834
Number of Inspections with non-monetary violations	1410	1102	845	1421	1478	1293	7549
% of inspections with a non-monetary violation	60.1%	57.9%	48.3%	54.0%	59.7%	46.3%	54.3%
% of inspections with more than 1 non-monetary violation	20.7%	18.4%	14.6%	17.0%	21.1%	13.7%	17.6%

CAD: Canadian dollars

Source: ESIS data 2012/2013 to 2017/2018.

Almost two-thirds of inspections during this period (65.3%) documented an ES violation. Over one-third (36.7%) yielded a monetary violation, and the incidence of a non-monetary violation was substantially higher (54.3%). Figure 1 shows how ES violations detected in inspections vary by business type across 13 common offences.

Figure 1.

Violation rate by violation and business type (2012/2013 to 2017/2018, pooled).

Businesses operating under franchised brands have higher violation rates among 10 of the 13 standards. Four of these are monetary, and the remaining six are non-monetary. Especially salient is the higher rate among franchised brands for violations concerning holiday pay, overtime pay, vacations, work hours, public holidays, and eating periods.

Table 2 gives a more comprehensive picture of violation rates by workplace type in Ontario. Overall, franchised brands have a substantially higher percentage of inspections yielding an ES violation (69% versus 64%). They also have a higher percentage of inspections yielding a monetary violation (62% versus 55% for other businesses).⁸ However, only specific types of monetary violations are more common among franchised brands: the failure to provide public holiday pay, overtime pay, or minimum wages (see Figure 1). Note that the mean and median value of monetary violations are substantially lower among franchised brands. While the corporate-owned locations in this category may be lowering the value of monetary violations, this may also reflect the significantly lower wages that predominate in the franchising sector.⁹ Regardless, both business types have similar repayment records for monetary violations (about 92%).

Table 2.

ES violation characteristics among workplace inspections, 2012/2013 to 2017/2018 (pooled).

Business type	Franchised brand		Other business		Total
Number of workplace inspections	3291		10,606		13,897
ES violation characteristics	%^a	N	%^a	N	%^a	N
Any violation	69.3	2281	64.1	6799	65.3	9080
Monetary violations	61.7	1400	54.7	3699	56.5	5099
Non-monetary violations	84.6	1921	83.3	5628	83.6	7549
More than 1 violation	74.2	1693	70.0	4759	71.1	6452
More than 1 monetary violation	29.8	420	32.7	1218	31.9	1638
More than 1 non-monetary violation	71.9	1384	67.8	3832	68.8	5216
Monetary violation paid in full	91.7	1281	92.1	3402	92.0	4683
Entitlement amount per inspection
Mean (CAD)	2349		4735		4080
Median (CAD)	696		905		834

ES: employment standards.

Source: ESIS data 2012/2013 to 2017/2018.

Not all column percentages are a function of the listed marginal totals because the number of valid cases varies for each tabulation.

Table 3 shows that the highest inspection rates for both business types was in accommodation and food, and retail. This is consistent with Ontario’s industry demographics more generally, where over 18% of establishments with employees are concentrated in these industries (Statistics Canada, 2016). Since these industries are reputed to have high levels of ES violations (Vosko, 2020), ESO’s may also be placing a higher priority on these industries for regular inspections and targeted blitzes. Historically, franchises have been popular in these industries, which also helps explain why the inspection rate for franchised brands is double the rate of other businesses in these industries.

Table 3.

Employer and inspection characteristics, 2012/2013 to 2017/2018 (pooled).

Business type	Franchised brand	Other business	Total
Number of workplace inspections	3291	10,606	13,897
Employer characteristics
Industry
Accommodation and food services	57.2%	25.4%	32.9%
Retail	32.6%	16.8%	20.5%
Primary industries^a, utilites, construction, transportation & warehousing, wholesale	0.9%	20.7%	16.0%
Professional, scientific and technical, finance, insurance and real estate, administrative and support services, waste management	2.2%	14.7%	11.7%
Educational services and public admin, health care, social assistance	1.1%	10.2%	8.1%
Other and personal services	4.2%	6.3%	5.8%
Information and culture, arts, entertainment and recreation	1.9%	5.9%	5.0%
Company size
Under 20 employees	53.5%	52.8%	53.0%
20–99 employees	22.2%	20.2%	20.7%
100+ employees	6.4%	7.3%	7.1%
Missing information	17.9%	19.6%	19.2%
Inspection characteristics
Type of inspection
Regular	25.5%	26.0%	25.9%
Expanded investigation	21.0%	22.5%	22.1%
Targeted/blitz	36.3%	30.9%	32.2%
Others	17.2%	20.7%	19.8%

Source: ESIS data 2012/2013 to 2017/2018.

Includes agriculture, forestry, fishing, mining, oil and gas.

Predicting the probability of violations by workplace type

We further analyse how business type explains the propensity for ES violations through binary logistic regression models that test each of our three hypotheses. That is, relative to other types of workplaces, franchisees: (1) are more likely to have an ES violation, (2) are more likely to have a monetary (wage) violation, and (3) are less likely to repay monetary violations.

Methods

Based on related research in Casey et al. (2018), our three models control for the influence of company size, industry, inspection type, and fiscal year. We also include the postal code of the inspection site to control for regional influences. Weil (2014) notes that minimum standards violations may be more likely in industries where labour comprises a significant portion of costs. Thus, we add interactions between business type and industry to control for the sensitivity to ES violations due to industry location. All three models use the same independent variables. However, since the decision to repay a monetary violation may partly depend on the amount owed, Model 3 also includes a control for the amount owed (logged), and its interaction with business type.

Results

The estimates from Models 1 to 3 are presented in Table 4. To facilitate interpretation, Figure 2 shows the predicted probabilities of a violation by business type and industry, for all violations. Figure 3 shows the same for monetary violations. Figure 4 compares the predicted probabilities of repaying a monetary violation by business type, across different amounts owed.

Table 4.

Binary logistic regressions for Models 1 – 3, 2012/2013 to 2017/2018 (pooled).

Model:	1		2		3
Dependent variable:	Any violation		Monetary violation		Repayment
	B	Odds	B	Odds	B	Odds
Workplace
(Other business type)
Franchised brand	.132	1.141	.189	1.208	−.822	.440
Workplace Size
(Under 20)
20–99	−.066	.936	.024	1.024	−.029	.971
100+	−.477	.621	−.460	.631	−.172	.842
Missing	−.205	.815	.011	1.011	−.196	.822
Industry
(Retail)
Accommodation and food services	.184	1.202	.176	1.192	−.273	.761
Primary ind^a, utils, const, mfg, transport and warehousing, wholesale	−.203	.816	−.359	.698	−.110	.896
Professional, scientific, technical, FIRE, admin and support, waste mgmt	−.064	.938	−.130	.878	.124	1.132
Personal and other services	.099	1.104	−.318	.728	−.288	.750
Educational services, public admin, health care and social assistance	−.432	.649	.190	1.209	−.253	.776
Information and culture, arts, entertainment and recreation	.287	1.332	.475	1.608	−.380	.684
Postal code
(M)
K	.582	1.790	.518	1.679	.227	1.255
L	.031	1.031	.353	1.423	−.419	.658
N	−.025	.975	−.181	.834	.478	1.613
P	.933	2.542	.169	1.184	−.546	.579
Missing	−.548	.578	−.193	.824	−1.752	.173
Inspection type
(Regular)
Expanded	.406	1.501	.406	1.501	−.276	.759
Targeted	−.151	.860	−.092	.912	.345	1.412
Other	−.782	.457	−.124	.883	−.051	.950
Fiscal year
(2012–2013)
2013–2014	−.193	.824	.104	1.110	−.314	.731
2014–2015	−.657	.518	−.226	.798	.409	1.505
2015–2016	−.355	.701	−.023	.977	−.031	.969
2016–2017	.106	1.112	−.208	.812	−.082	.921
2017–2018	−.357	.700	−.390	.677	−.356	.700
Franchised-brand x
(Retail)
Accommodation and food services	−.188	.829	−.074	.929	.436	1.547
Primary ind^a, utils, const, mfg, transport and warehousing, wholesale	−.203	.816	.308	1.361	−.909	.403
Professional, scientific, technical, FIRE, admin and support, waste mgmt	−.155	.856	−.224	.799	.265	1.303
Personal and other services	−.375	.687	.190	1.209	.323	1.381
Educational services, public admin, health care and social assistance	−.432	.649	.023	1.023	−.541	.582
Information and culture, arts, entertainment and recreation	−.051	.950	−.483	.617	−^b	−−
Amount owed(lnCAD)					.085	1.089
Amount owed(lnCAD) x franchised brand					.079	1.082
Intercept	.971	2.641	.106	1.112	2.372	10.719

Source: ESIS data 2012/2013 to 2017/2018.

Includes forestry, fishing, mining, oil and gas, utilities and manufacturing.

Insufficient cases to support a reliable interaction.

Figure 2.

Probability of a violation by business type and industry, 2012/2013 to 2017/2018 (pooled): company size < 20, workplace location = postal code M, inspection type = regular, fiscal year = 2012/2013.

Figure 3.

Probability of monetary violation by business type and industry, 2012/2013 to 2017/2018 (pooled): company size < 20, workplace location = postal code M, inspection type = regular, fiscal year = 2012/2013.

Figure 4.

Probability of repaying a monetary violation by business type and amount owed, 2012/2013 to 2017/2018 (pooled): company size < 20, workplace location = postal code M, inspection type = regular, industry = retail, fiscal year = 2012/2013.

The results in Figure 2 offer weak support for the first hypothesis. Only two of the seven industry groups show that franchised brands have a higher predicted probability of an ES violation (information and culture, and retail), and these probabilities are only marginally higher. Overall, the information and culture industry group has the highest overall probability of a violation for both business types, while the lowest overall probability is in education, public administration, healthcare, and social services.

The results in Figure 3 provide stronger support for Hypothesis 2. Among the seven industry groups, franchised brands have higher predicted probabilities of a monetary (wage) violation in all but two categories (information and culture, and professional, scientific and technical). The difference in probabilities favouring franchised brands is also comparatively larger in Figure 3 (ranging from .028 to .124 higher) than in Figure 2. Collectively, these results suggest that franchised brands may be more prone to monetary violations rather than just any type of ES violation.

Predicting non-repayment of monetary violations

Consistent with Hypothesis 3, franchisees are less likely than other businesses to repay monetary violations. Controlling for other factors, the odds of franchised brands repaying monetary violations are estimated to be only .440 times as great as other businesses (see Model 3 in Table 4). Alternately stated, the odds of other businesses repaying a monetary violation are therefore about 2.30 times greater than that of franchised brands. For additional perspective, Figure 4 shows the predicted probability of repaying a monetary violation at various amounts owing.

For both business types, the probability of repayment increases with the amount owed. However, franchised brands are still less likely than other businesses to repay a monetary violation, regardless of the amount. This gap is greatest at lower amounts (e.g. at ln CAD80, or the 10^th percentile), and narrowest at higher amounts (e.g. at ln CAD6766, or the 90^th percentile). Though franchised brands have the most improved probability of repayment at higher amounts owing, this may be of little comfort to employees because the number of monetary violations in franchising with a value at or above the 90th percentile is relatively small. According to the ESIS data for fiscal years 2012/2013–2017/2018, only 7% of monetary violations associated with franchised brands had a value that was at or above this level.

Discussion

Our findings are consistent with the theory that franchisees have a higher propensity for ES violations than other businesses. We have demonstrated this propensity by modelling the probability of ES violations among franchised brands versus other businesses in Ontario, between fiscal years 2012/2013 and 2017/2018. In theory, the architecture of franchising exerts marked pressure on business owners to extract profits from labour costs, thereby placing franchisees under more duress than other types of businesses to violate legal minimum ES in their respective jurisdictions (see Weil, 2014). Pursuant to this theory, we tested three relevant hypotheses, two of which are strongly supported by our findings.

Hypothesis 1 was that franchisees have a higher probability of violating ES than other businesses. First, the pressure to extract profits from labour costs is greatly facilitated by the asymmetric terms of franchising agreements. This pressure creates a set of operating conditions where franchisees may face tremendous pressure to take advantage of their workforce to remain profitable. Second, such behaviour is further facilitated by prevalence of precarious forms of employment in the franchising sector, which leaves franchise employees highly vulnerable to the actions of unscrupulous employers. Third, for many such employers, the benefits of disregarding ES tend to outweigh risks of being caught and sanctioned because of a weak ES enforcement regime.

Overall, the findings are consistent with Hypothesis 1. Net of influences related to industry, workplace size, region, inspection type, and fiscal year, franchisees have marginally greater odds of ES violations than other types of businesses. But there is no consistent support for this hypothesis across all industries. Only two of the seven industry groups (information, culture, arts, entertainment and recreation, and retail) had a higher propensity for ES violations among franchisees (see Figure 2). It is not surprising to see this hypothesis supported in retail, given the preponderance of franchising in this industry. But, uniquely, franchisees in information, culture, arts, entertainment and recreation had a higher probability of an ES violation than other businesses in this industry. This industry grouping is underrepresented in the ESIS data, with a low percentage of inspections among franchised brands (see Table 3). Notably, the food and accommodation industry was not among the industries where franchisees were more prone to ES violations, despite being an industry where franchising is common, and in which many inspections occurred (see Table 3).

There was strong support for Hypothesis 2, namely, that franchisees have a higher probability of monetary/wage-related ES violations than other businesses. Net of controls for workplace size, region, inspection type, and fiscal year, franchisees have greater odds of such violations. If franchisees were under pressure to illegally curtail labour costs, then one of the most effective ways of achieving this objective would be to violate ES provisions that have a more immediate and direct association with such costs (e.g. short-changing employees on wages, overtime, vacation, or holiday pay, or implementing unauthorised wage deductions). This employer tactic is supported by numerous examples in the literature in which the terms of franchising agreements lock business owners into dealing with employee costs on terms that are most beneficial to the franchisor, and with the effect of augmenting monetary violations. For example, see Elmore’s (2016) content analysis of US franchising agreements largely omitting any reference to a franchisee’s responsibilities regarding wage rates. Agreements often contain no-employee-poaching clauses from locations of the same brand, thereby barring franchisees from saving on training costs (Krueger and Ashenfelter, 2018). Further, Weil (2014) shows how agreements enabling franchisors to collect revenues and distribute profits can incentivise wage violations among franchisees.

Franchisees in five of the seven industry groups have higher propensities for monetary violations. This finding is in contrast to only two of the seven industry groups where franchisees have higher propensities for ES violations overall. One interpretation is that franchisees in Ontario at least, may be inherently more sensitive to monetary types of violations. This understanding fits with the theory and research that franchisees are under specific pressure to reduce labour costs. However, a comparison of Figures 2 and 3 also suggests that the propensity for a particular type of ES violation is highly contingent on the industry location of the business. It therefore reiterates the underlying role that industry structure plays in aggravating or protecting against labour market insecurity (see Weil, 2009).

More specific to franchising, it would be useful for future research to examine how the structures of different industries explain the propensity towards different types of ES violations. For example, there was surprisingly little evidence that franchisees in the accommodation and food industry group were more prone to ES violations in general (see Figure 2). However, franchisees in this same industry were substantially more likely to have a monetary violation than other types of businesses (see Figure 3). While our results support the view that franchisees are inherently more prone to monetary violations, the variability in the results across industries suggest that industry characteristics also play a role in the proneness of franchisees to different types of ES violations.

Hypothesis 3 posited that franchisees have a lower probability of repaying monetary/wage-related violations than non-franchises. The same incentives that encourage monetary violations among franchisees may also lower a franchisee’s probability of repaying the amount owed when an ES violation is detected. Also, ES enforcement regimes generally lack the resources to fully recover monies owed by offending employers. The absence of meaningful incentives to repay monies owed, along with weak deterrents against committing violations thus gives franchisees little economic reason to comply with repayment orders. Our results firmly support this hypothesis. Though there is some evidence that franchisees are more likely than other businesses to repay as the monetary violation increases in value, franchisees are still less likely to repay monetary violations than other types of businesses at any amount owed (see Figure 4).

Conclusion

Franchising is a prolific business model all over the world and can be found in almost every industry. Franchising is often recognised as a vehicle that creates wealth for expanding enterprises and aspiring entrepreneurs, but its architecture can also put disproportionate pressure on businesses to disregard ES. The economic benefits of franchising thus come largely at the expense of rank-and-file franchisee employees tied to local labour markets. We have investigated this fundamental problem in Ontario’s highly competitive and internationalised franchising sector. Of course, we can only speak to the consequences of franchising on ES violations in Ontario. It is possible that its effects in other provinces, or jurisdictions outside of Canada do not mirror what we have found here. Nevertheless, our findings are largely consistent with relevant theory and research on this issue. Moreover, the congruence of our findings with the prevailing studies centred on the US and European cases reinforces the credibility of concerns over the relationship between franchising and ES violations.

Among workplace inspections conducted in Ontario in fiscal years 2012/2013–2017/2018, franchisees are far more likely than other businesses to violate Ontario’s ESA when it comes to monetary violations. Of course, the severity of this behaviour varies by industry, and thus stresses the importance of industry characteristics for shaping how franchisees react to competitive pressures to lower labour costs. Franchisees are also less likely than other businesses to repay monetary violations. Since our data come from proactive workplace inspections that do not include reactively investigated complaints, and since we employ a conservative measure of monetary violations, our findings likely understate the full extent of this problem among Ontario’s franchised businesses.

What could be done to redress franchisees’ propensity for ES violations in Ontario, and other similar jurisdictions? A full solution is necessarily multifaceted and requires the cooperation of multiple stakeholders. Arguably stronger policy intervention is required to boost the effectiveness of ES enforcement regimes. Doing so sends a clear message to prospective offenders that the costs of being caught and sanctioned for ES violations outweigh the economic benefits. In practical terms, policy interventions should involve frontline initiatives such as deploying more ESOs to conduct proactive in-person inspections and follow up on complaints. They should also entail more consistent application of deterrence measures, such as the more regular levying of tickets and fines that impose economic penalties large enough to change an employer’s behaviour (e.g. see Casey et al., 2018; Tucker et al., 2019). Stronger deterrence measures may also be secured through more resources devoted to recovery in instances of monetary violations. In turn, these initiatives could be carried out within an enforcement framework that is more strategic in targeting industries and business types that have a greater likelihood of ES violations.¹⁰ Though there may be practical limits to the resources that governments can devote to these types of initiatives, organised labour may be able to help fill these gaps by becoming an active partner in Ontario’s ES enforcement regime (Vosko and Thomas, 2014).

Effective redress also involves adopting legislation that assigns franchisors and franchisees joint and several liability for workplace protections. By introducing such legislation, lead firms would be given a compelling economic reason to ensure that their franchisees comply with prevailing labour standards (see literature review section on shared liability). Other tools may include the prohibition of terms and conditions in franchising agreements that can compel franchisees to illegally save on labour costs in the first place. For example, this could be achieved by legislation requiring franchising agreements to allow franchisees more discretion over business operations and supply sources, product pricing, or royalties and fees.

More public disclosure of offending franchisees may also improve ES compliance. Averting damage to a company’s brand can be a major driver of regulatory compliance (Ayres and Braithwaite, 1992). In the ultra-competitive world of franchising, brand image is cardinal to success (Weil, 2014). Franchisors thus have a strong interest in controlling their outlets to minimise brand-damaging behaviours from opportunistic franchisees (Paik and Choi, 2007; Pizanti and Lerner, 2003). The positive effects of public disclosure policies are also supported by evidence. For example, this type of initiative is credited with improving the restaurant hygiene of franchised outlets in California USA (Jin and Leslie, 2009). As well, recent research by Kellner (2020) documents how the threat of expanded media reporting of ES violations motivated a major Australian café franchisor to be more involved in their franchisees’ compliance.

Proactive compliance deeds (PCD’s) have also been heralded as an innovation for improving franchisees’ ES compliance efforts (see Rawling, 2006). These are voluntary agreements between parties outlining a range of promises or commitments intended to rectify past contraventions, encourage future compliance, and shift some of the monitoring and enforcement to franchisors. PCD’s are innovative in that they capitalise on franchisors’ concerns with brand reputation, and on the hierarchy and resources of franchise networks to improve ES compliance (Hardy and Howe, 2015). Though the legal status of PCD’s is not entirely clear, they have been used with some success in the US and Australian franchising sectors (Hardy, 2018; Hardy and Howe, 2015; Vosko et al., 2016a). Ontario’s recent Changing Workplaces Review (Mitchell and Murray, 2017) also highly recommended implementing such top-down strategies, although the provincial government has yet to target franchisors in this way.

Legal strategies based on supply chain litigation have also showed promise in incentivising lead firms to ensure their independent outlets comply with labour laws. In this arrangement, goods and services from questionable supply chains are seized and assets frozen, compelling the lead firm to take more responsibility for labour standards (see Hardy and Howe, 2015). This strategy could also be modified to ensure compliance among franchise networks. For example, where questionable labour practices are evident, the state could interrupt the flow of royalties and fees from the offending franchisee to the franchisor until the latter takes more responsibility for ensuring its outlets are compliant with local labour standards.

Finally, Ontario can learn from Australia’s recent legislation expanding franchisor liability. In 2017, Australia amended the national Fair Work Act (FWA) with the Protecting Vulnerable Workers Act. Of note are s.550 and 558, which introduce accessorial liability to hold responsible any party knowingly involved in a contravention, including franchisors and their affiliates (for detailed discussion of these sections, see Hardy, 2018, 2019).

Unlike in Australia, the federal government cannot expand franchisor liability across provincial/territorial jurisdictions, as labour is largely a provincial matter in Canada. Consequently, amendments like s.550 and 558 of the FWA would need to be consistently introduced through provincial labour legislation across the country. That is, aside from the substantive challenges that these amendments have posed in the Australian context (see Hardy, 2019), the efficacy of an expanded liability law in Ontario would hinge on all 10 of Canada’s provinces (plus the federally regulated private sector) adopting similar legislation. Otherwise, culpable parties may continue to escape lability by establishing networks in provinces with weaker regulations applicable to franchising. Enforcement is also conceivably complicated by the substantial presence of internationally based franchise brands, most of which come from the contiguous US (see US Department of Commerce, 2018: 11). Consequently, many franchisors and their affiliates may be able to operate outside of Canadian labour laws, while their Ontario franchisees continue to face liability. The cooperation of both provincial and international jurisdictions is thus essential for similar expanded liability laws to be fully effective in Ontario.

Still, Ontario’s franchise regulations contained within the Arthur Wishart (Franchise Disclosure) Act (AWA) may hold some promise for expanding franchisor liability. Among other things, this act grants franchisees the right to seek damages from franchisors on various grounds, such as breaching the duty of fair dealing. Further research investigating the potential for franchisor liability on any such grounds in the context of ES violations is thereby desirable. For example, some scholars persuasively contend that franchisors essentially control wages by controlling every other variable in the franchisee’s business except wages (Ruckelshaus et al., 2014). From this perspective, monetary violations do not just reflect the actions of a legally independent business owner, but are the reasonable outcome of systemically one-sided franchise agreements. To what extent, then, could offending franchisees seek damages on the grounds that the franchisor has failed in their duty of fair dealing? Such innovative strategies to expand franchisor liability are especially needed considering that a 2017 amendment to the AWA is likely to increase the number of businesses falling under Ontario’s franchising legislation (Ronde, 2018).

The growing global popularity of franchising raises serious concerns about the future of workers’ rights and well-being not only in Canada, but elsewhere. If governments are already poorly equipped to enforce ES, as many are, then the threat posed by franchising to workers’ rights and entitlements is only going to grow as this activity continues to expand. The future trajectory of franchising’s expansion also fuels this concern. This business model is increasing in popularity in service industries such as retail, accommodation, food, and personal services – all industries where precarious employment is prevalent. Recently, franchising has been key for expanding these types of industries globally. As services continue to form an increasing part of the world’s economic activity, the ongoing expansion of franchising in service industries is expected. Consequently, in the absence of stronger ES enforcement regimes, substantially more front-line workers in Ontario and around the world are likely to become exposed to the competitive pressures wrought by franchising.

Footnotes

Acknowledgements

Authorship of this article is alphabetical.

Declaration of conflicting interests

The author(s) declares no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research on which this article is based was funded by the Government of Canada Social Sciences and Humanities Research Council of Canada Grant 895-2012-1014.

ORCID iDs

Mark D Easton

Andrea M Noack

Notes

Author Biographies

Mark D Easton is a Postdoctoral Visitor, working in the Closing the Employment Standards Enforcement Gap research partnership at York University, Toronto, Canada.

Andrea M Noack is Associate Professor of Sociology at Ryerson University, Canada. Her participation in community-engaged research includes investigating working conditions in Canada’s public sector, precarious work in Ontario and the enforcement of employment standards.

Leah F Vosko is Professor of Political Science and Canada Research Chair in the Political Economy of Gender and Work at York University, Toronto. She is known for her work in political economy and her writing on such topics as work, gender, citizenship, migration and labour markets and has published extensively on the reworking of the standard employment relationship, labour standards and the growth of precarious employment.

References

Ayres

Braithwaite

(1992) Responsive Regulation: Transcending the Debate. Oxford: Oxford University Press.

Bennett

(1994) Making Labour Law in Australia: Industrial Relations, Politics and Law. Sydney, NSW, Australia: Law Book Company.

Bernhardt

Milkman

Theodore

, et al. (2009) Broken Laws, Unprotected Workers: Violations of Employment and Labor Laws in America’s Cities. September. Chicago: Center for Urban Economic Development. Available at: https://www.nelp.org/wp-content/uploads/2015/03/BrokenLawsReport2009.pdf (accessed 7 September 2020).

Blair

Lafontaine

(2005) The Economics of Franchising. New York: Cambridge University Press.

Callaci

(2018) Vertical power and the creation of a fissured workplace: The case of franchising. Working Paper. University of Massachusetts. Amherst: Department of Economics. Available at: http://www.umass.edu/economics/sites/default/files/Callaci%20JMP%20revised%209_4_18.pdf (accessed 9 September 2020).

Callaci

(2019) Why Do Firms Impose Vertical Restraints? Evidence from Franchise Contracts. 489, July. University of Amherst: Political Economy Research Institute. Available at: https://www.peri.umass.edu/component/k2/item/1186-why-do-firms-impose-vertical-restraints-evidence-from-franchise-contracts (accessed 9 September 2020).

Canadian Franchising Association (2018a) 2018 Accomplishments Report. Toronto: Canadian Franchising Association. Available at: https://issuu.com/franchisecanada/docs/cfa_ar2019?e=32857347/69171575 (accessed 3 November 2020).

Canadian Franchising Association (2018b) Franchise Awareness – Franchising in Ontario: Policy Briefing. Toronto: Canadian Franchising Association. Available at: https://issuu.com/franchisecanada/docs/policybriefing_2018_on?e=32857347/61710137/ (accessed 25 October 2019).

Canadian Franchising Association (2019) 2019 Accomplishments Report. Toronto: Canadian Franchising Association. Available at: https://issuu.com/franchisecanada/docs/cfa_ar2019?e=32857347/69171575 (accessed 3 November 2020).

10.

Casey

Tucker

Vosko

, et al. (2018) Using tickets in employment standards inspections: deterrence as effective enforcement in Ontario, Canada? The Economic and Labour Relations Review 29(2): 228–249.

11.

Clibborn

Wright

(2018) Employer theft of temporary migrant workers’ wages in Australia: why has the state failed to act? The Economic and Labour Relations Review 29(2): 207–227.

12.

Combs

Ketchen

Jr Short

(2011) Franchising research: Major milestones, new directions, and its future within entrepreneurship. Entrepreneurship Theory and Practice 35(3): 413–425.

13.

Curran

Stanworth

(1983) Franchising in the modern economy – towards a theoretical understanding. International Small Business Journal 2(1): 8–26.

14.

Dant

Kaufmann

(1999a) Preface to the special issue on franchising. Journal of Business Venturing 14(1): 1–3.

15.

Dant

Kaufmann

(1999b) Introduction to the special issue on franchising. Journal of Business Venturing 14(4): 321–322.

16.

Davidov

(2015) Indirect employment: Should lead companies be liable. Comparative Labor Law Policy Journal 37(1): 5–36.

17.

Elmore

(2016) The future of fast food governance. University of Pennsylvania Law Review Online 165(1): 73–90.

18.

Elmore

(2018) Franchise regulation for the fissured economy. The George Washington Law Review 86(4): 907–965.

19.

Frazer

Grace

(2017) Franchisor-franchisee relationships. In: Hoy

Rozenn

Terry

(eds) Handbook of Research on Franchising. Research Handbooks in Business and Management. Northampton, MA:: Edward Elgar, pp. 211–233.

20.

Fried

Elango

(1997) Franchising research: A literature review and synthesis. Journal of Small Business Management 35(3): 61–81.

21.

Friend

(n.d) Canadian franchise statistics. Available at: http://www.franchise101.net/canadian-franchise-statistics (accessed 15 November 2019).

22.

Griffith

(2019) An empirical study of fast-food franchising contracts: Towards a new ‘intermediary’ theory of joint employment. Washington Law Review 94(1): 171–216.

23.

Grünhagen

Witte

(2005) The role of franchising as a driver of economic development for emerging economies. Journal of Business, Industry and Economics 5(1): 27–45.

24.

Hardy

(2018) Big brands, big responsibilities: An examination of franchisor accountability for employment contraventions in the United States, Canada, and Australia. Comparative Labor Law & Policy Journal 40(2): 285–324.

25.

Hardy

(2019) Shifting risk and shirking responsibility? The challenge of upholding employment standards regulation within franchise networks. Australian Journal of Labour Law 32(1): 62–82.

26.

Hardy

Howe

(2015) Chain reaction: A strategic approach to addressing employment noncompliance in complex supply chains. Journal of Industrial Relations 57(4): 563–584.

27.

Hoy

(2017) Research contributions to understanding franchising. In: Hoy

Rozenn

Terry

(eds) Handbook of Research on Franchising. Research Handbooks in Business and Management. Northampton, MA: Edward Elgar, pp. 1–14.

28.

Hoy

Shane

(1998) Franchising as an entrepreneurial venture form. Journal of Business Venturing 13(2): 91–94.

29.

Hunt

(1972) The socioeconomic consequences of the franchise system of distribution. Journal of Marketing 36(3): 32–38.

30.

Weil

(2015) The impact of franchising on labor standards compliance. Industrial and Labor Relations Review 68(5): 977–1006.

31.

Jin

Leslie

(2009) Reputational incentives for restaurant hygiene. American Economic Journal: Microeconomics 1(1): 237–267.

32.

Kellner

(2020) Determinants of human resource management strategy in a franchise. In: Dundon

Wilkinson

(eds) Case Studies in Work, Employment and Human Resource Management. Cheltenham: Edward Elgar, pp. 32–38.

33.

Kellner

Peetz

Townsend

, et al. (2016) ‘We are very focused on the muffins’: Regulation of and compliance with industrial relations in franchises. Journal of Industrial Relations 58(1): 25–45.

34.

Krueger

Ashenfelter

(2018) Theory and Evidence on Employer Collusion in the Franchise Sector. NBER Working Paper 24831, July. Cambridge, MA: National Bureau of Economic Research.

35.

Lafontaine

(2005) Franchise Contracting and Organization. Business Economics. Northampton, MA: Edward Elgar.

36.

Lafontaine

(2014) Franchising: Directions for future research. International Journal of the Economics of Business 21(1): 21–25.

37.

Lewchuk

(2017) Precarious jobs: Where are they, and how do they affect well-being? The Economic and Labour Relations Review 28(3): 402–419.

38.

Maconachie

Goodwin

(2010) Employer evasion of workers’ entitlements 1986–1995: why, what and whose? Journal of Industrial Relations 52(4): 419–437.

39.

Michael

(2014) Can franchising be an economic development strategy? An empirical investigation. Small Business Economics 42(3): 611–620.

40.

Mitchell

Murray

(2017) The Changing Workplaces Review: An Agenda for Workplace Rights, Final Report. Available at: https://files.ontario.ca/books/mol_changing_workplace_report_eng_2_0.pdf (accessed 9 September 2020).

41.

Noack

Vosko

(2011) Precarious Jobs in Ontario: Mapping Dimensions of Labour Market Insecurity by Workers’ Social Location and Context. November. Law Commission of Ontario. Available at: https://www.lco-cdo.org/wp-content/uploads/2012/01/vulnerable-workers-call-for-papers-noack-vosko.pdf (accessed 9 September 2020).

42.

Paik

Choi

(2007) Control, autonomy and collaboration in the fast food industry: A comparative study between domestic and international franchising. International Small Business Journal 25(5): 539–562.

43.

Pizanti

Lerner

(2003) Examining control and autonomy in the franchisor-franchisee relationship. International Small Business Journal 21(2): 131–159.

44.

Polanco

Zell

(2017) English as a border-drawing matter: Language and the regulation of migrant service worker mobility in international labor markets. Journal of International Migration and Integration 18(1): 267–289.

45.

Rawling

(2006) A generic model of regulating supply chain outsourcing. In: Arup

Gahan

Howe

, et al (eds) Labour Law and Labour Market Regulation: Essays on the Construction, Constitution and Regulation of Labour Markets and Work Relationships. Sydney, NSW, Australia: Federation Press, pp. 520–541.

46.

Ronde

(2018) Ontario government makes changes to Ontario’s franchise legislation. Cassels Brock & Blackwell LLP. Available at: https://cassels.com/?export=pdf&post_id=3257&force (accessed 24 July 2020).

47.

Ruckelshaus

Smith

Leberstein

, et al. (2014) Who’s the Boss: Restoring Accountability for Labor Standards in Outsourced Work. May. New York: National Employment Law Project. Available at: https://www.nelp.org/wp-content/uploads/2015/02/Whos-the-Boss-Restoring-Accountability-Labor-Standards-Outsourced-Work-Report.pdf (accessed 7 September 2020).

48.

Sanghavi

(1998) Franchising as a tool for small medium sized enterprises (SME) development in transitional economies-the case of central European countries. Management Research News 21(11): 35–44.

49.

Sanjukta

(2019) Fissuring and the firm exemption. Law and Contemporary Problems 82(2): 65–87.

50.

Shane

Hoy

(1996) Franchising: A gateway to cooperative entrepreneurship. Journal of Business Venturing 11(5): 325–327.

51.

Stanworth

Curran

(1999) Colas, burgers, shakes, and shirkers: Towards a sociological model of franchising in the market economy. Journal of Business Venturing 14(4): 323–344.

52.

Statistics Canada (2016) Canadian Industry Statistics, special tabulation, unpublished data, unclassified excluded. Statistics Canada. Available at: https://www.ic.gc.ca/app/scr/app/cis/summary-sommaire/72 (accessed 11 November 2019).

53.

Statistics Canada (n.d.a) Table 14-10-0297-01 labour force characteristics by occupation, annual, inactive (x 1,000). Available at: https://www150.statcan.gc.ca/t1/tbl1/en/cv.action?pid=1410029701 (accessed 25 October 2020).

54.

Statistics Canada (n.d.b) Table 17-10-0009-01 population estimates, quarterly. Available at: https://doi.org/10.25318/1710000901-eng (accessed 25 October 2020).

55.

Steinbaum

(2019) Antitrust, the gig economy, and labor market power. Law and Contemporary Problems 82(3): 45–64.

56.

Tucker

Vosko

Casey

, et al. (2019) Carrying little sticks: Is there a ‘deterrence gap’ in employment standards enforcement in Ontario, Canada? International Journal of Comparative Labour Law 35(1): 1–30.

57.

US Department of Commerce (2016) Franchising: A Market Assessment Tool for US Exporters. May. Washington, DC: International Trade Administration, Industry and Analysis. Available at: https://www.export-u.com/INDUSTRIES/Franchising_Top_Markets_Report.pdf (accessed 12 October 2019).

58.

US Department of Commerce (2018) Franchising Industry: A Reference for U.S. Exporters. Washington, DC: International Trade Administration, US Commercial Services. Available at: https://www.franchising.com/ta.php?id=4335&url=https://www.franchise.org/sites/default/files/USCS_Franchising_Resource_Guide_2018.pdf (accessed 7 September 2020)

59.

Utgård

Nygaard

Dahlstrom

(2015) Franchising, local market characteristics and alcohol sales to minors. Journal of Business Research 68(10): 2117–2124.

60.

Vosko

(2020) Closing the Enforcement Gap: Improving Employment Standards Protections for People in Precarious Jobs. Toronto, ON, Canada: University of Toronto Press.

61.

Vosko

Grundy

Thomas

(2016a) Challenging new governance: Evaluating new approaches to employment standards enforcement in common law jurisdictions. Economic and Industrial Democracy 37(2): 373–398.

62.

Vosko

Grundy

Tucker

, et al. (2017) The compliance model of employment standards enforcement: an evidence-based assessment of its efficacy in instances of wage theft. Industrial Relations Journal 48(3): 256–273.

63.

Vosko

Noack

Thomas

(2016b) How Far Does the Employment Standards Act, 2000, Extend and What Are the Gaps in Coverage? An Empirical Analysis of Archival and Statistical Data. Prepared for the Ontario Ministry of Labour to support the Changing Workplaces Review of 2015, March. Available at: https://cirhr.library.utoronto.ca/sites/cirhr.library.utoronto.ca/files/research-projects/Vosko%20Noack%20Thomas-5-%20ESA%20Exemptions.pdf (accessed 7 September 2020)

64.

Vosko

Thomas

(2014) Confronting the employment standards enforcement gap: Exploring the potential for union engagement with employment law in Ontario, Canada. Journal of Industrial Relations 56(5): 631–652.

65.

Watson

(1997) Golden Arches East: McDonald’s in East Asia. Stanford, CA: Stanford University Press.

66.

Weil

(2009) Rethinking the regulation of vulnerable work in the USA: A sector based approach. Journal of Industrial Relations 51(3): 411–430.

67.

Weil

(2011) Enforcing labour standards in fissured workplaces: The US experience. The Economic and Labour Relations Review 22(2): 33–54.

68.

Weil

(2014) The Fissured Workplace: Why Work Became So Bad for So Many and What Can Be Done to Improve It. Cambridge, MA: Harvard University Press.

69.

Welsh

DHB

Alon

Falbe

(2006) An examination of international retail franchising in emerging markets. Journal of Small Business Management 44(1): 130–149.

70.

World Franchise Council (2019) Survey on the Economic Impact of Franchising Worldwide (2018). Unpublished, WFC Summit October 21–27, 2019, Abu Dhabi, Unites Arab Emirates.