“The Relationship Between Part-Time Employment and Firm Performance, and the Impact of HRM Practices”

MSc Thesis in Business Administration – Small Business &

Entrepreneurship

Student: Giovanni Riefolo – s2746697

Supervisor: Prof. dr. Haibo Zhou

“The Relationship Between Part-Time Employment

and Firm Performance, and the Impact of HRM

Practices”

Faculty of Economics and Business, Department of Innovation Management and

Strategy

Abstract

Despite the rising popularity of part-time employment arrangements, the effect of this contractual forms on company performance is still unclear. Also, the effect that HRM good practices such as incentives and benefits have on the relationship between part-time employees and company performance has not been investigated extensively. The aim of this research is to try to untangle the effect that part-time employees have on company performance, whether this effect is non-linear and if HRM practices, together with control variables such as firm size and sector, have both a direct and a moderating effect on the above-mentioned relationships. The results indicate that the effect of part-timers on company performance might indeed be non-linear. Also, certain HRM benefits have been found not only to have a positive impact on company performance when granted to part- as well as full-time employees, but also to moderate the relationship between part-timers and company performance. The control variables have also been found to have an impact (to various extents) in the statistical model developed in this research.

Acknowledgements

Many thanks to my supervisor, Prof. dr. Haibo Zhou for her precious advices and suggestions, and to the Head of the department of Innovation Management & Strategy at the University of Groningen, Prof. dr. Maryse Brand for the help received in gathering the necessary data. I would also like to thank the Ewing Marion

Table of Contents

Introduction ………..……….………...………

The Evolution of Part-Time Employment ….………..

Literature Review .………...………

1. The Impact of Part-time Employment ………

₅

2. The Impact of Human Resource Management ………..………..

₇

3. Sector-Related Effects ……….….….….….….….………..

₈

4. Firm Size-Related Effects ………..………..

₉

Theoretical Framework .………..………..…….………..

Methodology ……….………

Analysis and Results ………..………

Discussion …….……….………

Limitations & Conclusion ……..……….………

Introduction

In the last two decades the industrialized economies experienced a significant growth in the percentage of part-time workers. In the EU the growth has been fairly stable as opposed, for instance, to the aggregate growth experienced in the total OECD labour market (OECD, 2015a). Despite the importance of the phenomenon, scholars and academics did not investigate extensively the impact that it bears on the economy (Künn-Nelen et al., 2013; Pauka, 2015). Indeed, still many incongruences exist between what human capital theory states concerning alternative use of employment contracts and the empirical evidences about the impact of part-time employment on company performance (Künn-Nelen et al., 2013; Pauka, 2015; Michie & Sheehan-Quinn, 2001; Roux, 2007; Valverde et al., 2000). It is still ambiguous the effect that part-time employment arrangements have on company performance and how this effect varies according to industry and sector-related differences, and to different shares between part-time and full-time employees in the workforce, or whether such effect is moderated by firm size, firm-sector and human resource practices. While the effects related to the design and implementation of HRM benefits and incentives has been widely studied over the years both in small and larger companies (Ng & Maki, 1993; Wagar, 1998; Kotey & Slade, 2005; Heneman & Berkley, 1999; De Kok & Uhlaner, 2001), the effect of said benefits on different types of employees has not been extensively analyzed. In the same way, it is not clear whether variables as firm size and sector affect the relationship between part-timers and company performance. As it will be further explained in the next section, the high growth rate in the amount of part-timers (as compared to full-timers within a company) especially in western economies, raises questions concerning the optimal way in which part-time working arrangements should be designed and implemented: both policy makers and business owners would find it beneficial to understand how certain contextual factors (HRM, firm size and sector, in the specific case of this research) play a role in determining whether certain contractual arrangements are convenient or not to the company, or whether a certain amount of part-time employees is beneficial. In particular, understanding such relationship in the context of MSMEs is even more important if we consider that MSMEs account for more than 95% of enterprises across the world, and 99% in the EU, generating more than 67% of employment (Wymenga et al., 2012; Ayyagari et al., 2011).

Therefore, the aim of this research is to evaluate the effect that different shares of part- and full-time employees have on micro, small and medium-seized enterprises (MSMEs) financial performance. Concerning MSMEs, it will be shown in the literature review section how part-time employment can determine an improvement either in terms of productivity through allocation efficiencies (Owen, 1978; Montgomery, 1988) or increase job satisfaction which ultimately leads to increased productivity.

Still according to existing literature, it is reasonable to believe that Human Resource practices might have a moderating effect between the effect of part-timers on financial and innovative outcomes. It will also be investigated which, above the different HR practices, is more likely to strengthen the above mentioned relationship. Existing researches also suggest industry-related effects. The study will be hence held from a

business perspective (rather than an entrepreneurship perspective), and will be performed using the NORC

Data Enclave - Kauffman Foundation Database (‘KFS - Kauffman Firm Survey Data’) which gathered data about American firms founded in 2004 and tracked them over their early years of operation.

Before proceeding any further an important distinction needs to be done. There is often a general misunderstanding when talking about the different contractual arrangements: part-time employment refers to those contractual arrangements which take place over a prolonged period of time, in which the employee agrees to work for only a limited amount of hours during the week. Differently from part-time contracts there exist numerous alternative employment arrangements, which have also been studied extensively over the past two decades (Davis-Blake & Uzzi, 1993; Matusik & Hills, 1998; Mitlacher 2008): these are often referred to as

employs independent contractors, on-call employees and temporary help agency employees. Alternative employment arrangements are different from part-time employment arrangements in the sense that they do not rely on a prolonged working relationship, but are rather restricted to a predefined timespan. As a consequence alternative forms of employment can not be considered to be substitutive of the long-term working relationships: if on one hand is true that non-standard (external) employment arrangements are beneficial to those firms that have to cut costs in the short-run, on the other hand the growth of non-standard employment arrangements is problematic for the economy as a whole, as it does not offer significant protection and benefits to the worker (Kalleberg et al., 1997; 2000; Lepak et al., 2003): SOLIDAR, a European network of 52 NGOs whose task is to advance social justice rights in the EU, collected evidences supporting the thesis that alternative working arrangements slowly eroded protection and social rights across the whole European labour market (Cremers, 2010).

Even from a business perspective, some scholars suggest that the externalization of labour may bring issues related to the firm’s long-term horizon, as it makes more difficult the development and retention of core skills and capabilities, all key factors for the creation and sustentation of a competitive advantage (Lei & Hitt, 1995). For the above-mentioned reasons, devoting attention to standard employment forms (employees on the company’s official payroll, both part-time and full-time) and on their impact on company performance is relevant not only to policymakers, but also to employers and workers. Indeed, as stated by Feldman (1990), investigating the phenomenon of part-time employment is necessary for at least two distinct reasons: first, entire industries heavily (if not exclusively) rely on part-time working arrangements in order to satisfy their need for a greater flexibility, such as the service sector; second, three different demographic sectors, namely

younger workers (16-24 years old), older workers (Over 65) and female workers, perceive part-time

employment as an important source of labour.

The Evolution of Part-Time Employment

According to the OECD (2015b) data, in the European Union the part-time working arrangements were on average slightly above 14% of total employment in 1994, and grew to a total 17.5% of total employment in 2014. The growth is even more significant when we look at the aggregate values for all the OECD economies in figure 1 below:

Indeed, in the OECD economies the rate grew from an 11.9% out of total employment in 1994, to almost 17% in 2014. The sharp difference in the growth rate magnitude during the 2001/2002 period between the EU and the OECD countries is given by the increase in part-time employment in every country comprised in the G8 group, in particular in the US labour market (OECD, 2015a). In fact, in the US labour market the growth of part-time employment was significantly faster and of greater magnitude than the one experienced within the EU. According to the US Department of Labor’s Bureau of Labor Statistics, the number of workers under a part-time status doubled during the 2009 financial crisis. Figure 2b shows how the loss in full-time employment has been captured by the increase in part-time employment in the US labour market:

Figure 2a & 2b: Part-time Employment Evolution in the US in Thousands and Percentage (Source: data.bls.gov/)

Figure 2a on the left shows the variation in part-time employment (measured in thousands of workers), while figure 2b shows in percentage terms the increase in part-time as opposed to the decrease in full-time employment. During recessive periods (shadowed in grey in figure 2b) we notice that there is a rapid switch form full-time to part-time labour demand, which is consistent with the difference in labour costs for the two statuses: Lettau (1997) found evidences that full-time employees’ compensations are on average up to 25% higher than part-time compensations. Also, part-timers can expect much lower benefits per hour. This is why in the short-term, during recessive periods, companies tend to change the shares of part- and full-time employees in order to rapidly cut labour cost expenses. Furthermore, another increase in the part-time employment rate is expected to be generated in the next years in the US as a side-effect of the recent health care reform, the Patient Protection and Affordable Care Act (PPACA): according to the reform, starting from the 1st of January 2015 employees who work more than 30 hours per week are entitled to health coverage (US Department of Health & Human Services, 2015). The American HR Magazine (2013) collected evidences showing how companies were getting ready to face the new provisions set forth by the new reform, and one of the responses was to cut full-time contract in order to rely heavily on part-time contracts up to 29 working hours per week.

Concerning the type of companies that will be the object of this research, the EU definition for SMEs is based on a first parameter accounting for the size of the company’s workforce, and a second parameter, which could either be total company turnover or the balance sheet total (EC, 2015):

Company N° of Employees Turnover BS Total

Medium < 250

≤ €50m

≤ €43m

Small < 50

≤ €10m

≤ €10m

Micro < 10

≤ €2m

≤ €2m

Table 1: Parameters for the Definition of SMEs in the EU (Source: ec.europa.eu)

The US definition for SMEs however is not universally applicable to all firms, but it rather distinguishes different parameters for different sectors. In the US, businesses defined as small can employ between 50 and 1,500 employees, and can exhibit a turnover up to $29 Millions, depending on the sector in which it operates. In this research, because of the need to establish a clear, distinguishable definition of SMEs, it will be employed the generally accepted definition of American SMEs that would result from the application of the first EU parameter:

Company N° of Employees

Medium

≤ 499

Small

≤ 100

Micro

≤ 10

Table 2: Parameters for the Definition of SMEs in the US

In the present study, part-timers are defined as those employees in the official company payroll (therefore without including contract workers) whose working performances do not exceed the limit of 35 hours per week. Conversely, employees exceeding said limit are considered as full-time workers.

Literature Review

1. The Impact of Part-time Employment

Part-timers are hence more likely to reduce firm performance as they accumulate a lower amount of human capital (Negrey, 1993; Pauka 2015). This view however is not always supported by concrete evidences, and the overall effect of part-timers on firm performance remains ambiguous: while investigating the effect that part- and full-time employment has on personal utilities, some Authors found a positive correlation between part-full-time status and job satisfaction (Booth and van Ours, 2008), which can ultimately affect firm performance through increased productivity.

Moreover, the classic stream of literature concerning part-time employment (Owen, 1978; Montgomery, 1988) theorized that a potential improvement in productivity could come from part-time employment as it allows for

allocation efficiency: this term refers to the minimization of inactive workers due to a momentary lack of the

demand, hence applicable to all those sectors which are subject to high fluctuations in customer demand (Mabert & Showalter, 1990). On the other hand the same stream of literature also states that large shares of part-timers might lower firm productivity (hence following human capital theory), which undermines the

allocation efficiencies effect, thus providing misleading expectations on the impact of part-timers on firm

financial and innovative performance.

Concerning the impact on firm’s financial performance, Garnero et al. (2014), using a Belgian dataset, found evidences supporting the thesis that part-time employment has a positive effect on firm performance. In particular, the authors distinguished between different kind of part-timers, small PT (less than 15 working hours per week), medium PT (between 15 and 24 working hours per week) and large PT (more than 24 but less than 30 working hours per week) and their analysis shows a positive effect of large PT on company performance, measured in value added compared to full-time workers. Also Michie & Sheehan-Quinn (2001) found part-time employment to have a statistically positive significant impact on firm performance.

In contrast, other researchers obtained different results concerning the effect of part-time employment on firm performance: Valverde et al. (2000) did not find any statistically significant effect on firm performance (measured in firm’s profits and competitive advantage) for any analyzed employment mode (part-time, fixed-term, subcontracting, and annualized hours usage employment), arguing that the non-significance of the results is inextricably linked to the complex nature of employment.

Pauka (2015), using a dataset on German firms, found that firms employing part-time employees have a lower financial performance than firms employing full-time workers. As for Garnero et al. (2014), also in this study a distinction is made between small, medium and large PT, and small PT have been found to have the strongest negative effect on firm performance. The author attributes the results of the research to the argumentations provided by human capital theory, according to which financial performance is also a function of companies’ investments in human capital.

Other studies instead focused on the effect that part-time employment has on firm innovativeness: Giannetti & Madia (2013) through an examination of innovative practices (restricted only to product innovations) in Italy, calculated in terms of marginal sales coming from product innovations, found a positive effect between part-time employment and firm innovativeness. On the other hand, Michie and Sheehan-Quinn (2001) and Arvanitis (2005) found a significantly negative impact of part-time employment on innovative performance (even with process innovations in Arvanitis’ study).

allocation efficiency. The view held in this study is that the two views can be view as complementary of each

other: if on one hand there is an actual need for flexibility (particularly when there are high fluctuations in customer demand) and for allocation efficiency, on the other hand it is undeniable the importance of core skills and capabilities that employees need to possess and possibly develop over time within an organization. This in turn means that there is a trade-off between organizational efficiency and employees’ marginal productivity in designing and managing the workforce formation. Based on this reasoning however smaller businesses might experience greater costs associated with greater amount of part-timers: issues related to the uncertain commitment that part-timers are more likely to have toward their job (Chapman, 1995), might make SME’s owners to favor higher shares of full-timers, meaning that the ratio should be in favor of full-timers. The problem under investigation in this research is not whether part-timers have or not a direct effect on company performance, but rather what is the optimal share of part- and full-timers that allows to minimize the costs of this trade-off for SMEs. It can therefore be expected that a certain share of part-timers is needed inside organizations, but that such share needs to be neither irrelevant nor too substantial, otherwise the existing literature would have exhibited at least a common direction in terms of results, rather than resulting in contrasting outputs. As a consequence, the non-linear effect of part-timers on performance will be tested. In fact, in the first step of the analysis part-timers will be accounted for through the ratio of part- to full-timers in a company, in order to measure the impact of part-timers while still taking into account the complementary effect of full-time employees. As has been pointed out in this first literature section, it is reasonable to expect that the marginal positive effect of part-timers on performance tends to decrease as the number of part-time employees rises. Therefore, it can be expected that such relationship will not be linear.

Following this reasoning, the following hypotheses can be presented: H1a: The effect of Part-timers on financial performance is non-linear. H1b: The effect of Part-timers on competitiveness is non-linear.

2. The Impact of Human Resource Management

When discussing about the potential effects that certain types of employment bear on company performance, one cannot avoid to take into account those company’s characteristic that may impact on the final output of its employees. In this sense, there is a broad consensus over the fact that human resource management (HRM) practices are partly accountable for firm performance (Fabi et al., 2007; Hansen & Wernerfelt, 1989). This view follows the resource-based theory of the firm, as ‘the HR function, through either directly controlling or

strongly influencing the characteristics of human resources in organizations, plays an important role in developing and maintaining a firm's competitive advantage’ (Barney & Wright, 1998).

For MSMEs, the topic of HRM practices have been found to be particularly relevant. Many scholars have found convincing evidences about the indirect importance that SMEs’ owners and managers attach to practices aimed at stimulating employee retention (Ng & Maki, 1993), communication and employee participation (Golhar & Deshpande, 1997) or the availability of quality workers (Hornsby & Kuratko, 2003). As aforementioned, HRM practices can strengthen the causal relationship between such kind of operational-related utilities and company performance. Bryson (1999) found a positive relationship between HRM practices with both communications with employees and overall firm performance.

But why investigating how HRM practices moderate the effect of timers on company performance, if part-timers are by definition entitled to less benefits vis-a-vis the full-part-timers? Because some practices might be more effective then others, and might buffer the loss in productivity assumed within human capital theory while still being a cheaper and more flexible working arrangement.

Recalling the importance of HR management as set forth by Human Capital theory, one could theorize that certain HRM practices (such as incentives, paid insurance and sick leaves) might buffer for the reduced human capital possessed by part-timers: by fostering a sense of belonging to the company and enhancing productivity, it is believed in this research that HRM practices will have a moderating effect on the primary impact that part-timers yield on financial and innovative firm performance. It can be expected that said practices will strengthen the primary effect. Therefore, the following hypotheses can be formulated:

H2a: HRM practices will have a positive moderating effect on the impact of part-timers on a company financial

performance.

H2b: HRM practices will have a positive moderating effect on the impact of part-timers on a firm’s

competitiveness.

3. Sector-Related Effects

Künn-Nelen et al. (2013) investigated the effect that different shares of part- and full-timers have on service-firm productivity. The authors used a Dutch dataset containing data of the pharmaceutical sector and found evidences that ‘firms with a larger part-time employment share are more productive’ than those with a larger full-timers share. More precisely, firms with a 10% larger share of part-timers exhibit a greater productivity between 2.9% and 6%, and in their view this difference is mainly attributable to allocation efficiencies, arguing part-timers can serve as a buffer to compensate for high demand fluctuations. The Authors also suggests that, as part-time labour demand is higher in those industries and sectors where the operating hours exceed the 30-hours limit set for full-timers (Owen, 1978; Montgomery, 1988), part-time employment is much more likely to have a significant effect on service rather than product firms. This is also justified through the percentage of people employed which ranges from an EU average of 70% to a US average of 80%. Also Roux (2007) found that part-time hourly productivity is higher than full-time productivity, especially in the service sector. Based on the above mentioned evidences, it can be expected that the effect of part-timers on company performance will be much stronger in the service-sector:

H3a: The sector in which the company operates is expected to moderate the effect between part-timers and

H3b: The sector in which the company operates is expected to moderate the effect between part-timers and

competitiveness, which will be stronger for firms operating in the service-sector.

4. Firm Size-Related Effects

Concerning the use of part-time employment in MSMEs there is a literature gap: although part-timers identify a large share of the working population (both in EU and the US) and MSMEs account for more than 90% of businesses worldwide there has been no research investigating the effect of part-time employment within this business setting. Nonetheless, based on what has been said previously concerning the trade-off between organizational flexibility and human capital development, it is reasonable to theorize that the same would apply also to those firms with a restricted workforce. Issues, consistently with human capital theory, are raised by the uncertain commitment part-timers have to their job, and to the possible lack of experience and resources needed to perform a certain task (Chapman, 1995). For this reasons, small firms might not want to undertake the risk of hiring many part-timers, even though such form of employment would be less binding and less expensive to a small business owner. It would hence be reasonable to believe that the effect of part-timers on company performance is stronger in larger rather than small firms:

H4a: Firm size will moderate the effect of the relationship between part-timers and financial performance,

which will be stronger in larger firms, compared to smaller organizations.

H4b: Firm size will moderate the effect of the relationship between part-timers and competitiveness.

Theoretical Framework

Figure 3: The Conceptual Model

On the left lies our independent variable. In the box below it can be seen the moderating variable HRM, which will be constructed as a dummy variable in the first test, while subsequently each HRM practice/benefit will be made explicit in the regression through a categorical variable to assess what is the effect each of them bears. In the upper box there are the control variables, firm size and sector.

Methodology

Sample and Data

The Ewing Marion Kauffman Foundation surveyed more than 4900 American firms which started their operations in 2004, and tracked them over the years with yearly follow-ups to the original survey. The random sample was originally selected from a broader population of more than 32000 firms randomly selected from the Dun & Bradstreet’s database list. The KFS is one of the largest longitudinal databases of recent businesses. For the present research, however, the data contained in the latest follow-up, performed in 2011, has been used. Moreover, the dataset used for the analysis has been adapted through a logical imputation of missing data, as the KFS questionnaire in many cases presents complementary items for the same variable: for example, the amount of part-timers in a company is either equal to item ‘How many part-timers are currently in the official

payroll of the Company?’ or it can be logically derived by subtracting the number of full-time employees from

the total workforce of the company. In this way the number of missing values attributable to typos or errors made by respondents while filing the survey.

Below, a list of the variables that have been used in this study:

Profits: Company profits measured in American dollars. Only contains positive values since losses are not

considered in this item. This variable will be the IV of the first analysis.

Competitive Advantage (dummy): Variable which takes on value 1 if the company possesses a competitive

advantage (that could be in the forms of patents, trademarks, copyrights or other advantages identified by the business owner), 0 otherwise. This variable will be the IV of the second analysis.

Profitability (dummy): Variable whose value is equal to 1 if the company managed to end the previous

financial period with a positive amount of net profits, 0 if the company totaled losses in the previous period. This variable will be used in the robustness check.

Part-Timers Ratio: This variable has been obtained dividing the amount indicated by the company concerning

the number of part-time employees on the official company payroll, by the corresponding amount of full-timers hired.

HRM (dummy): Variable obtained by creating a dummy variable whose value is equal to 0 if the company

HRM (categorical): This variable takes on value 1 if the company offers a health plan to part-timers; 2 if a

retirement plan is offered; 3 for a stock options bonus; 4 for the grant of a bonus incentives plan; 5 for tuition reimbursement offered to part-timers; 6 if the company offers paid vacations; 7 for paid sick days; 8 if the company offers alternative working schedules for part-timers, and 9 if the company offers generically other benefits; 0 if the company does not offer any of the above mentioned benefits to its part-time workforce.

Sector (dummy): This variable takes on value 1 if the company operates in the service sector, 0 if the company

operates in the product sector.

Firm Size (categorical): Firm_Size = 1: Micro, if Tot_Employees i [0 ; 10]

2: Small, if Tot_Employees i (10 ; 100]

3: Medium, if Tot_Employees i (100 ; 500]

Since the majority of firms included in the dataset are micro firms (up to 10 employees) the first group indicating micro firms has been used as a reference group throughout the analyses.

First Analysis

The first analysis is constituted by a multiple regression. In the first step of the regression, part-timers are not divided into different shares, but will be rather employed as a continuous variable, in which it will be tested the non-linearity of the effect. In fact, the study provided by Künn-Nelen et al. (2013) does not tests the hypothesis that such effect is non-linear, and consequently the results are not generalizable (or externally

valid). It has to be noted however that using only the number of part-timers in a company as a continuous IV

would be misleading, as it would not take into account the differential effect that part- and full-timers have on a company’s financial performance. In order to solve for this problem, the ratio of part- to full-timers in a company can be used as a mean to jointly test the effect of both forms of employment: as already stated during the literature review section, in most organizations part-time and full-time employees work complementarily, which means that their coexistence in the workplace needs to be taken into account. Therefore, the PT_ratio variable needs to be recorded:

PT_ratioi = (Part_Time_Employees)i / (Full_Part_Time_Employees)i

The first step of my analysis will imply a third order regression analysis, which can be written as follows:

Ln(Net_Profits) = β0 + β1 (PT_Ratio) + β2 (PT_Ratio)2 + β3 (PT_Ratio)3 + β4 (HRM) + β5 (Sector) + β6 (firm_size) + β7 (PT_Ratio*HRM) + β8 (PT_Ratio*Sector) + β9 (PT_Ratio*firm_size) + εi

β0 Is the constant term, β1 is the linear effect of the part-timers’ ratio on financial performance while β2 is the quadratic term and β3 is the cubic term. These two terms are expected to correct the linear effect of part-timers on financial performance, which would otherwise be potentially infinite (that is, if such effect results to be positive, without a non-linear term for correction of the linear effect there is no limit to the positive marginal effect, which would keep growing stably to the infinite). This analysis will allow to test H1a, that is, whether the effect of part-timers on financial performance is non-linear. Coefficients β4, β5 and β6 represent respectively

the moderating variable and the two control variables in this research. Coefficients β7, β8 and β9 instead are the

The first analysis presents 5 distinct models, one per each hypothesis except H2 for which two distinct models are needed (first HRM will be inputted as a dummy, subsequently as a categorical variable).

Second Analysis

In order to test H1b, H2b, H3b, and H4b a different kind of analysis is needed, as the dependent variables could not be operationalized in a continuous (non-binary) fashion: A logit regression is used to calculate the regression coefficients in the case of a linear probability model. A LPM is simply a regression model in which the dependent variable is binary. Therefore, a Logit regression will be used as it relies on the standard cumulative probability distribution function (CDF), hence avoiding non-sense outcomes (Hair et al., 2010). The last steps of the analysis can therefore be depicted as follows:

Pr[CA = 1] = Φ [β0 + β1 (PT_ratio) + β2 (PT_Ratio)2 + β3 (PT_Ratio)3 + β4 (HRM) + β5 (Sector) + β6 (firm_size) + β7 (PT_Ratio*HRM) + β8 (PT_Ratio*Sector) + β9 (PT_Ratio*firm_size)] + εi

Φ indicates the standard cumulative distribution function, while the betas refer exactly to the same variables as in the first analysis. Also in this analysis, I will develop the six models plus the base model 0. In this way it will be possible to estimate how the different variables impact on the company’s likelihood to develop a competitive advantage over its competitors.

Robustness Check

In order to further validate and countercheck the findings, I will test again the hypotheses concerning financial performance using a logit model. In this case the dependent variable will not be inputted as a continuous variable, but rather as a dummy variable (Company Profitability =1 if the company made net profits, =0 otherwise). My third analysis can therefore be expressed as follows:

Pr[Profit = 1] = Φ [β0 + β1 (PT_Ratio) + β2 (PT_Ratio)2 + β3 (PT_Ratio)3 + β4 (HRM) + β5 (Sector) + β6 (firm_size) + β7 (PT_Ratio*HRM) + β8 (PT_Ratio*Sector) + β9 (PT_Ratio*firm_size)] + εi

As for the first two analyses, betas and variables do not change, except for the DV. Moreover, also the robustness check will be performed in the same fashion as the first two analyses, with a base model 0, a linear, non-linear and moderating models.

Analysis & Results

First Analysis

The first hypotheses to be tested involves checking whether the direct impact that part-timers have on firm performance is non-linear.

in the independent variable xi is associated with a 100(βi)% change in the dependent variable yi. Below the results of the first analysis:

Ln(Profits) H1A H2A H2A+ H3A H4A

Constant 10.753** 10.734** 10.724** 10.830** 10.725** 0.135 0.137 0.138 0.141 0.136 PT Ratio -0.476* -0.409 -0.354 -0.672** -0.618** 0.259 0.255 0.252 0.283 0.283 PT Ratio^2 0.080 0.080 0.075 0.095 0.201** 0.066 0.065 0.065 0.067 0.097 PT Ratio^3 -0.005 -0.005 -0.005 -0.005 -0.010* 0.004 0.004 0.004 0.004 0.005 HRM (dum) 0.174 0.262 0.204 0.174 0.192 0.215 0.192 0.193 Sector (dum) -0.117 -0.123 -0.143 -0.265 -0.120 0.173 0.173 0.176 0.190 0.173

Firm Size (cat):

Micro - - - - - Small 1.450** 1.438** 1.491** 1.442** 1.746** 0.250 0.250 0.242 0.249 0.247 Medium 2.428** 2.424** 2.420** 2.421** 2.384** 0.463 0.468 0.524 0.466 0.512 HRM (cat): Health Plan -2.860 3.066 Retirem. Plan 1.037* 0.533 Stock Options 1.710** 0.239 Bonus Plan 1.308** 0.391 Tuition Reimb. -0.421 0.419 Paid Vacation 0.752* 0.386

Paid Sick Days 0.067

0.601

0.244 Other 0.016 0.612 Pt_Ratio*HRM -0.128* 0.077 Pt_Ratio*Sector 0.268** 0.123 Pt_Ratio*Micro Omitted - Pt_Ratio*Small -0.639** 0.236 Pt_Ratio*Med 0.521 0.539 Pt_Ratio*Health 0.878 1.000 Pt_Ratio*Retirem -0.625 0.728 Pt_Ratio*Stock Omitted - Pt_Ratio*Bonus -0.723 0.768 Pt_Ratio*Tuition -0.047 0.206 Pt_Ratio*Vacat. -0.693** 0.298 Pt_Ratio*Sick 0.654 1.037 Pt_Ratio*Flex -0.078 0.079 Pt_Ratio*Other -0.298 0.181

** Coefficients are significant at the 5% level of significance * Coefficients are significant at the 10% level of significance

Values in Italic represent the Robust Standard Errors

Table 3: Results for The First Analysis

concerning the non-linear effect. Moreover, the direct, linear effect of part-timers is negative, indicating that as the ratio goes up (hence as the amount of part-timers becomes larger vis-à-vis the amount of full-timers) the financial performance of the company are expected to decrease.

The second column contains the results of the second regression model: even though the direct effect of HRM benefits on company financial performance is not significant, it is possible to see that there is indeed a moderating effect of HRM benefits on the part-timers – profit relationship. This effect, however, is negative, indicating that as the ratio of part- to full-timers increases, the effect of HRM benefits granted to part-timers becomes even smaller. It is therefore possible to (partially) accept H2a based on this result. In the third column the HRM-related model is run again, this time including the categorical instead of the dummy variable indicating benefits. Apart from the firm size variable which is still strongly significant, indicating that small firms are expected to perform better than micro firms, and medium-seized companies to perform on average better than small firms, it is possible to see how four out of nine benefits are statistically significant: retirement plans, stock options, incentives bonus plans and paid vacations have been found to positively affect financial performance of a company directly. Concerning the moderating effect however, only one of the interaction effects related to the three significant benefits has been found to be statistically significant, namely the one concerning paid vacations: it can be stated that if one one hand the grant of paid vacations to part-time employees has a positive direct effect on financial performance, the interaction effect tells us that as the ratio of part-timers increases, the effectiveness of the paid vacation benefit becomes smaller.

Regarding the sector effect, the results present a slight inconsistence: the direct effect of the sector in which the company operates on financial performance is not significant. However, the moderating term is strongly significant, indicating that as the ratio of part-timers grows within a company operating in the service sector, the impact on financial performances becomes stronger. This is in line with what was expected after the literature review: consistently with the results obtained by Künn-Nelen et al. (2013) and Roux (2007) it can not be rejected the null hypothesis that service sector firms do benefit from higher shares of part-timers in their workforce.

Similarly, the results concerning the last hypothesis about the moderating effect of firm size partially reflect what was expected after the literature review: beside the direct effect of firm size, whose significance is stable throughout the whole analysis indicating that medium-seized firms on average can expect greater profits than small firms, which can expect a better financial performance with respect to micro firms, the moderating effect about part-timers and small-seized firms is significant. Recalling that micro businesses have been used as the reference level, as the ratio of part-timers grows within a small-seized company, the effect of its size on company performance becomes weaker. However, this only confirms part of my hypothesis: on one hand, it is confirmed that is much harder for smaller companies to benefit from large shares of part-timers, but on the other it is not confirmed that larger organizations do benefit from the presence of certain shares of part-timers in their workforce, even if the positive sign of the coefficient might reveal that this could indeed be the case. Moreover, in this last model it is also possible to notice how the direct non-linear effects of part-timers on company performance becomes significant, revealing that it might indeed be the case that the impact of part-timers on company performance is not linear.

Second Analysis

Below the results of the second analysis, performed as a logit analysis (the sub-models resemble the ones of the first analysis):

Comp.Adv. H1B H2B H2B+ H3B H4B Constant 0.220* 0.213 0.251* 0.251* 0.211 0.131 0.131 0.133 0.139 0.132 PT Ratio -0.072 -0.056 -0.055 -0.150 -0.097 0.214 0.211 0.220 0.255 0.222 PT Ratio^2 -0.007 0.002 0.003 0.0001 0.021 0.064 0.064 0.065 0.070 0.074 PT Ratio^3 0.002 0.002 0.001 0.002 0.002 0.004 0.004 0.004 0.005 0.005 HRM (dum) 0.431** 0.482** 0.443** 0.423** 0.171 0.201 0.172 0.172 Sector (dum) -0.574** -0.577** -0.636** -0.633** -0.575** 0.149 0.149 0.152 0.173 0.149

Firm Size (cat):

Micro - - - - - Small 0.156 0.148 0.103 0.150 0.265 0.189 0.189 0.195 0.189 0.209 Medium 0.099 0.092 -0.031 0.094 -0.184 0.645 0.646 0.724 0.650 0.701 HRM (cat): Health Plan 0.963 0.935

Retirem. Plan Empty

-

Stock Options Empty

- Bonus Plan 0.949 0.749 Tuition Reimb. -34.954** 4.046 Paid Vacation -0.329 0.697

Paid Sick Days 0.112

0.643

0.237 Other 1.026* 0.582 Pt_Ratio*HRM -0.072 0.154 Pt_Ratio*Sector 0.109 0.169 Pt_Ratio*Micro Omitted - Pt_Ratio*Small -0.224 0.180 Pt_Ratio*Med 2.680 2.153 Pt_Ratio*Health -1.060 0.705 Pt_Ratio*Retirem Omitted - Pt_Ratio*Stock Omitted - Pt_Ratio*Bonus -0.579 0.853 Pt_Ratio*Tuition 35.671** 5.051 Pt_Ratio*Vacat. -0.042 0.539 Pt_Ratio*Sick -1.522 1.177 Pt_Ratio*Flex -0.074 0.166 Pt_Ratio*Other -0.132 0.265

** Coefficients are significant at the 5% level of significance * Coefficients are significant at the 10% level of significance

Values in Italic represent the Robust Standard Errors

Table 4: Results for The Second Analysis

basis of these results, also considering that also the direct effect of part- to full-timers ratio has not been found to be statistically significant.

Concerning the direct and moderating effect of HRM benefits, the overall results are in line with the ones obtained in the previous analysis: in the second column, where the variable indicating HRM benefits granted to part-timers is inputted as a dummy, it is glaring that there is indeed a positive direct effect on the likelihood that the company has or will develop a competitive advantage. The interaction term, however, is not significant, meaning that the model is not able to capture a moderating effect when multiple forms of employee benefits are grouped together in one dummy variable. Nonetheless, in the third column it can be noticed that three out of nine benefits do have a direct effect on company competitiveness, namely tuition reimbursement, flexible

working schedules and the generic other benefits. Of these three, tuition reimbursement has also been found

to moderate the effect between part-timers and firm competitiveness. Also in this case, as for the first analysis, it it not possible to fully reject H2b, since there are indicators that there could indeed be a moderating effect, as the grant of tuition reimbursement might reveals.

Concerning the third hypothesis it can be seen that there is indeed a direct effect of the sector variable, indicating that is on average harder for service-firms to be competitive vis-à-vis their product-sector counterparts. However, H3b has to be rejected since there is no statistically significant interaction effect with part-timers.

Also the last hypothesis H4b concerning firm size and the moderating effect between part-timers and firm competitiveness has to be rejected: neither the direct nor the interaction effects related to firm-size have been found to be statistically significant. This in turn indicates that when it comes to the development and retention of a competitive advantage, the amount of workers employed by the company alone does not allow to make estimates on the likelihood that said advantage will be developed.

Robustness Check

In order to counter verify the main preliminary findings of this research, the following logit analysis has been developed. As explained in the methodology section, here the DV is the profitability-dummy variable, while the different models resemble the ones developed in the previous analyses, in which each model follows an hypothesis (except for hypothesis 2 for which, as usual, two different models have been developed. Concerning the first hypothesis, based on the first analysis I did not find supporting evidences. The robustness analysis, however, identifies a strongly significant non-linearity concerning the effect of part-timers. Both the quadratic and the cubic term are in fact significant at the 5% level of significance.

Concerning the second hypothesis the results of the robustness check resemble the ones of the first analysis: when using the dummy variable to indicate HRM benefits, there is neither a significant direct nor moderating effect on financial performance. However, when using the categorical variable, there is indeed a significantly negative direct effect for both retirement plan and paid vacations granted to employees. Concerning the moderating effect, both benefits are heavily counterbalanced by significantly positive interaction terms, meaning that as the ratio of part- to full timers grows, the overall effect of the benefits on financial performance becomes easily positive (recalling that in the first analysis these two items where both significantly positive, but only paid vacations had a significant moderating effect on financial performance).

Concerning the fourth hypothesis involving firm size, the robustness analysis did not reveal any significant outcome, neither for the direct nor for the moderating effect of firm size.

Discussion

The first hypothesis concerning the non-linear effect of part-timers on company performance did not produce results which are strong enough to reject the alternative: in the first analysis only the direct effect of part-timers on financial performance was found to be statistically significant. However, the robustness check was able to capture a strongly significant non-linear effect of part-timers on company performance throughout all the steps of the analysis (that is, the non-linear terms are statistically significant at the 5% level of significance in any of the five regression models). This in turn reveal that there might be a non-linear effect of part-timers on company performance, but further research is needed in order to strengthen this judgment. H1a can therefore be only partially accepted (given the particularly strong results of the robustness check), while H1b has to be rejected, as the second analysis did not reveal any non-linear effect of part-timers of company competitiveness. A similar reasoning can be applied also to the second set of hypotheses: in both the first and the third (robustness) analysis the effect of HRM benefits when grouped together is not significant. When explicated, however, some of the benefits have been found to be statistically significant in both their direct and moderating effect. In particular, the grant of retirement plans, stock options, bonus plans and paid vacations to part-time employees have been found to directly affect financial performance, while paid vacations and retirement plans have also been found to have a moderating effect on the relationship between part-timers and financial performance. The results concerning the effect of HRM benefits is important as it reveals that many benefits, when granted to part-timers, might actually have a negative impact on company performance: this could be the reason why I did not find any statistically significant impact of HRM benefits when these where all grouped together through a dummy variable. In fact, when each benefit has been treated independently from each other, many benefits have been found to have a direct effect on financial performance when granted to part-timers, and some of these also showed a significant moderating effect. Hence H2a can only be partially accepted. Concerning HRM benefits and competitiveness, there has been found a statistically significant direct effect of HRM benefits granted to part-timers on company competitiveness when inputting the dummy variable in the model, but no statistically significant moderating effect was found. Also in this case, when treated independently, tuition reimbursements and flexible working schedules have been found to directly affect firm competitiveness, and tuition reimbursements also showed a significant moderating effect. In this case it can be applied the same reasoning previously applied to H2a: H2b can only be partially accepted, but these results offer a significant contribution revealing how the study of the impact of HRM benefits needs to be targeted at explicit benefits, since grouping all benefits together might bear misleading results. It has also be shown how certain benefits are able to either buffer the negative direct impact on company performance when part-timers are taken into account, or even to strengthen the direct relationship.

profitability but no moderating effect with the amount of part-timers. With these premises, H3a can hence be accepted, meaning that the sector in which the company operates does indeed affect the impact of part-timers on financial performance.

H3b on the other hand can not be accepted, as the second analysis only found a statistically significant direct effect of sector on firm competitiveness. In particular, service-based companies are found to be much less likely to possess or develop a competitive advantage compared to product-companies:

Pr[CA = 1| Service-Sector] = Φ(0.251-0.633) = 35%

Pr[CA = 1| Product-Sector] = Φ(0.251) = 60%

This means that, ceteris paribus, a product-company has a 25% greater probability to develop a competitive advantage with respect to service firms. This could easily be related to the fact that is much easier to design and to develop improvements for products (which would fall either into copyrights, patents or trademarks) than it is for services. Nonetheless, there was no statistically significant coefficient confirming a moderating effect between sector and part-timers when it comes to competitiveness. Therefore, H3b can be rejected. Lastly, concerning firm size, H4a can only be partially accepted: both small and medium seizes have been found to have a direct effect on financial performance, but the moderating effect with part-timers has only been found for small companies. In particular, consistently with human capital theory (Chapman, 1995) smaller companies have been found to suffer from larger shares of part-timers more than larger companies. However, the non-completeness of the results only allows for a partial acceptance of H4a.

The relationship between firm-size, part-timers and competitiveness instead is not statistically significant, meaning that a firm degree of competitiveness might not be linked to its size: in Theory of Economic Development (1912) Schumpeter defined what is today known as the Schumpeter Mark I perspective, according to which the entrepreneurs setting up new firms critically contribute to the degree of competitiveness of an industry. Also other researches propose that competitiveness might not be affected by firm size, but rather by the degree of productivity of a company (Dolfsma & van der Velde, 2014). H3b can therefore be rejected.

Limitations & Conclusion

The present research is among the first which tries to untangle the effect of part-time employment on a company’s competitive and financial performance, using an instrument which takes into account the simultaneous coexistence of both part- and full-time workers. Moreover, it is among the first which attempts to link the effect of part-time employment on firm performance to the grant of HRM benefits to part-timers. As such, it presents an initial contribution to the study of part-time employment. The analysis has been carried out using the data provided by the Ewing Marion Kauffman Foundation – NORC Data Enclave at the

University of Chicago concerning US-based businesses founded in the early years of the millennium.

performance relationship is crucial, as it has been shown how these kind of instruments could potentially make a difference on the overall ability of a company to be profitable.

Nonetheless, it has been shown how part-timers might actually have a non-linear impact on financial performance (recalling that H1a was only partially accepted), and how certain HRM benefits are able to moderate the relationship between part-timers and both financial and competitive company performance: in the specific case, the grant of retirement plans, stock options, bonus plans and paid vacations to part-time employees have been found to directly affect financial performance, while paid vacations and retirement plans have also been found to have a moderating effect on the relationship between part-timers and financial performance. Concerning competitiveness of a company, tuition reimbursement and flexible working

schedules have been found to positively have an impact on such performance, with the first one being also able

to moderate the effect between part-timers and the achievement of a competitive advantage. Moreover, it has been showed how, consistently with the theoretical argumentations provided, the sector in which a company operates does affect the relationship between part-timers and performance. Also, firm size has been found to partially affect said relationship when financial performances are considered, but not in the case of firm competitiveness, strengthening the provisions set forth by human capital theory.

References

Allen Smith, J.D., (2013). The Rise of the ‘Part-Time Society’. HR Magazine, 66(8).

Arvanitis, S. (2005). Modes of labor flexibility at firm level: Are there any implications for performance

and innovation?. Evidence for the Swiss economy, Industrial and Corporate Change, 14(6), 993-1016.

Ayyagari, M., Demirgüç-Kunt, A. and Maksimovic, V. (2011). Small vs. Young Firms Across the World

– Contribution to Employment, Job Creation, and Growth. Policy Research Working Paper 5631 (The

World Bank Development Research Group).

Barney, J., (1991). Firm Resources and Sustained Competitive Advantage, Journal of Management 17(3), 99-120.

Barney, J. & Wright, P. M., (1998). On Becoming a Strategic Partner: The Role of Human Resources in

Gaining Competitive Advantage, Human Resource Management 37(1), 31-46.

Bryson, A., (1999). The Impact of Employee Involvement on Small Firms’ Financial Performance, National Institute Economic Review 169(7), 78-95.

Brynjolfsson, E. & McAfee, A., (2011). Race Against the Machine: How the Digital Revolution Is

Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy. Digital Frontier Press.

Chapman, E.N., (1995). Achieving Job Satisfaction: Helping Employees Reach Higher Productivity. Crisp

Learning Publications.

Chelius. J. & Smith, R. S., (1990). Profit Sharing and Employment Stability. Industrial and Labor Relations Review 43(3), 256-73.

Cremers, J. (2010). Non-standard employment relations or the erosion of workers’ rights. SOLIDAR Briefing Paper #23.

Davis-Blake, A., & Uzzi, B. (1993). Determinants of employment externalization: A study of temporary

workers and independent contractors. Administrative Science Quarterly, 38, 195–223.

Dean, A. and Kretschmer, M. (2007). Can Ideas be Capital? Factors of Production in the Postindustrial

Economy: A Review and Critique. Academy of Management Review, 32, 573-594.

De Kok, J. and Uhlaner, L.M. (2001). Organization Context and HRM in the Small Firm. Small Business Economics, 17, 273-291.

Dolfsma, W. and van der Velde, G. (2014). Industry Innovativeness, firm size and entrepreneurship:

Schumpeter Mark III?. Journal of Evolutionary Economics, 24(4), 713-736.

Fabi, B., Raymond, L and Lacoursiere, R., (2007). HRM practice clusters in relation to size and

performance: an empirical investigation in Canadian manufacturing SMEs, Journal of Small Business

and Entrepreneurship, 20(1).

Feldman, D. C. (1990). Reconceptualizing the nature and consequences of part-time work. Academy of Management Review, 15, 103–112.

Garnero, A.; Kampelmann, S.; Rycx, F. (2014). Part-Time Work, Wages and Productivity: Evidence from

Belgian Matched Panel Data. Industrial & Labor Relations Review, 67(3), 926-954.

Giannetti, C.; Madia, M. (2013). Work arrangements and firm innovation: is there any relationship? Cambridge Journal of Economics,37(2), 273-297.

Golhar, D. Y. & Deshpande, S. P.. (1997). HRM Practices of Large and Small Canadian Manufacturing

Firms, Journal of Small Business Management, 35(3), 30-38.

Hansen, G.S. & Wernerfelt, B., (1989). Determinants of Firm Performance: The Relative Importance of

Economic and Organizational Factors, Strategic Management Journal 10(5), 399-411.

Heneman, H.G. & Berkley, R.A., (1999). Applicant Attraction Practicesand Outcomes among Small

Businesses, Journal of Small Business Management, 37(1), 53-74.

Hornsby, J. S. & Kuratko, D. F., (1990). Human Resource Management in Small Business: Critical Issues

for the 1990s, Journal of Small Business Management, 8(3), 9-18.

Kalleberg, A. L., Rasell, E., Cassirer, N., Reskin, B. F., Hudson, K., Webster, D., Appelbaum, E., and Spalter-Roth. R. M., (1997). Nonstandard Work, Substandard Jobs: Flexible Work Arrangements in

the U.S., Washington, DC: Economic Policy Institute.

Kalleberg, A. L., Reskin, B. F. and Hudson, K., (2000). Bad Jobs in America: Standard and Nonstandard

Employment Relations and Job Quality in the United States. American Sociological Review, 65(2),

256-278.

Kotey, B. & Meredith, G. G., (1997). Relationships among Owner/Manager Personal Values, Business

Strategies, and Enterprise Performance, Journal of Small Business Management 35(2), 37-64.

Kotey, B. & Slade, P., (2005). Formal HRM Practices in Small Growing Firms, Journal of Small Business Management 43(1), 16-40.

Kunn-Nelen, A., de Grip, A. and Fouarge, D., (2013). Is Part-Time Employment Beneficial for Firm

Productivity?. Industrial and Labor Relations Review, 66(5), 1172-1191.

Leeflang, P., Bijmolt, T., Pauwels, K and Wieringa, J., (2014). Modeling Markets: Analyzing Marketing

Phenomena and Improving Marketing Decision Making. New York: Springer, International Series in

Quantitative Marketing, Vol. 1.

Lei, D., & Hitt, M. A., (1995). Strategic restructuring and outsourcing: The effect of merger and

acquisitions and LBOs on building firm skills and capabilities. Journal of Management, 21, 835-860.

Lepak, D. P., Takeuchi, R., & Snell, S. A. (2003). Employment flexibility and firm performance:

Examining the interaction effects of employment mode, environmental dynamism, and technological intensity. Journal of Management, 29, 681-703.

Lettau, M. K., (1997). Compensation in part-time jobs versus full-time jobs, What if the job is the same?. Economics Letters 56, 101-106.

Mabert, V., & Showalter, M., (1990). Measuring the Impact of Part-Time Workers in Service

Organisations, Journal of Operations Management, 9(2), 209–229.

Martínez-Sánchez, A., Vela-Jiménez, M.-J., Pérez-Pérez, M. & de-Luis-Carnicer, P., (2011). The

Dynamics of Labour Flexibility: Relationships between Employment Type and Innovativeness. Journal

of Management Studies, 48(4), 715-736.

Matusik, S. F., & Hill, C. W. L. (1998). The utilization of contingent work, knowledge creation, and

competitive advantage. Academy of Management Review, 23, 680-697.

Mitlacher, L. (2008), Job quality and temporary agency work: Challenges for human resource

management in triangular employment relations in Germany, International Journal of Human

Resource Management, 19(3), 446-460.

Michie, J. & Sheehan-Quinn, M. (2001): Labour Market Flexibility, Human Resource Management and

Corporate Performance. British Journal of Management, 12(4), 287-306.

Montgomery, M., (1988). On the determinants of employer demand for part-time workers. Review of Economics and Statistics 70(1), 112–17.

Negrey, C., (1993). Gender, Time, and Reduced Work. Albany, NY: State University of New York Press. Ng I. & Maki, D. (1993). Human Resource Management in the Canadian Manufacturing Sector, The

International Journal of Human Resource Management 4(4), 897-916.

Pauka, K., (2015). How does Part-time Work Affect Firm Performance and Innovation Activity?. WWZ Working Paper (University of Basel).

Roberts, J. M., (2013). The Future of Jobs. Economic Development Journal, 12(3)

Roux, S., (2007). Les gains de la flexibilité d´emploi pour les entreprises: le travail à temps partiel et de

courte durée. Reflets et Perspectives de la Vie économique, 46(2), 117-140.

Schumpeter, J.A., (1912). The Theory of Economic Development: An Inquiry into Profits, Capital, Credit,

Interest and the Business Cycle. New Brunswick (U.S.A) and London (U.K.): Transaction Publishers.

Valverde, M.; Tregaskis, O.; Brewster, C. (2000). Labor Flexibility and Firm Performance, International Advances in Economic Research,6(4), 649-661.

Wagar, T.H., (1998). Determinants of HRM Practices in Small Firms: Some Evidence from Atlantic

Canada, Journal of Small Business Management, 36(2), 13-23.

Welbourne, T.M. & Cyr, L.A., (1999). Using Ownership as an Incentive, Group and Organization Management 24(4), 438-60.

Wymenga, P., Spanikova, V., Barker, A., Konings, J. and Canton, E. (2012). EU SMEs in 2012: At the

Crossroads. Annual Report on Small and Medium-sized Enterprises in the EU, 2011/12, Report for

the European Commission.

Online References

European Community (2015). Definition of MSMEs, EC Website: http://ec.europa. eu/growth/smes/business-friendly-environment/smedefinition/index_en.htm

OECD (2015a). OECD Data. Online Reference Address: https://data.oecd.org/emp/part-time-employment-rate.htm.

OECD (2015b), OECD Labour Force Statistics 2014, OECD Publishing. http://dx.doi.org/10.1787/oecd_lfs-2014-en.

US Bureau of Labor Statistics (2015). Bureau of Labor Statistics Data. Online Reference Address: http://data.bls.gov/pdq/SurveyOutputServlet.