This section commences by defining a gainsharing programme. Its framework for employee participation is explained, and the experiences of US-based companies using a gainsharing programme conclude it.

According to Armstrong (2010), gainsharing is a formula based company wide programme that offers employees a share in the financial gains of a company as a result of its improved performance. Employee involvement is a cornerstone in the success of the gainsharing programme. The involvement is systematic as employees are involved at all the stages of implementation including the design and periodic evaluation (Armstrong 2010). For gainsharing to be successful, Masternak (2009) concurs that it must link two of the most important areas in organisational behaviour, namely employee participation and positive employee involvement. Under gainsharing schemes, knowledge sharing is formalised through an employee suggestion system. Workers are encouraged to participate in various ways. For instance, they write down their cost-saving ideas and submit them to a committee, generally made up of employee and management representatives, who determine the viability of the suggestion (Masternak 2009). The monetary savings from implemented suggestions are calculated using a formula based on historical cost data. These savings become part of a pool of money that is distributed to all participating employees in the form of a gainsharing bonus or reward (Henemen & Von Hippel 2005). Although the financial element is a key feature of gainsharing, its strength as a process for improving performance lies in other important features such as ownership, involvement and communication (Armstrong 2010).

The participation structure of gainsharing varies by organisation and tends to grow and evolve over time (Masternak 2009). Initially, involvement may be as small as conducting regular communication meetings or as major as forming self-directed work teams (Armstrong & Stephens 2005). However, Rondeau (2007) notes that team-based suggestion systems are common gainsharing participation structures. Basically, employee involvement teams are formed to solicit and review performance improvement suggestions from other members of the workforce. The groups are permanent and meet on a regular basis to approve and implement ideas within their spending authority. Suggestions that are approved by teams, but are beyond its spending authority, are advanced to a higher level review or steering teams.

Roman (2009) investigated how making changes to a team-based incentive programme affected productivity, product quality and absenteeism in three large manufacturing plants in Texas (in the USA). Results indicated that there were significant improvements in all of these areas. Furthermore, the investigation noted that changes in organisations must be linked to changes in incentive schemes if they are to be continuously successful. Irrespective of the employee involvement system the organisation chooses, it is critical that all the problems or challenges are addressed, questions are answered and employee ideas are given proper consideration. Hietpas (2008), in a study of gainsharing in the building industry in the USA, identified employee involvement at all stages of programme implementation as vital. Hietpas (2008) noted that meetings between middle- and upper management and employees must take place frequently so that discussions about important issues do not get ignored. The aforementioned are key issues in separating gainsharing successes from gainsharing failures.

Gainsharing in various sectors of economic activity is increasing (Weiss 2006). It is regarded as a compensation system that includes employees in plans to improve performance so that they (and management) share any gains. Bowey (2003) contends that companies without clearly stated objectives generally have unsuccessful compensation plans. Successful companies, in contrast operate their plans as part of a holistic approach, involving senior management support and a wide range of team-building, performance management and communication initiatives. As a result, gainsharing should be viewed as a complex organisational development intervention and not simply as an incentive system (Matthew & Sanjiy 2005). As such, gainsharing programmes are not quick fixes to inherent problems but are devices that take advantage of a focused organisational strategy that combines employee participation and an incentive system. Fundamentally, gainsharing rewards motivate employees and save the company money (Gardner 2011). Hence, if high productivity is required over a short period, incentives offered are better than the normal pay.

Employees under gainsharing reward structures are expected to engage in more cooperative behaviours, including sharing their ideas for saving costs and improving production, more so than employees under more competitive, individual-based compensation systems (Tjosvold 2004). Gainsharing offsets one of the downsides of flatter structures, namely fewer promotion opportunities. It raises the level of both intrinsic and extrinsic rewards, particularly for that portion of the workforce that is predisposed to making an extra effort. It helps motivated employees take a keener interest in organisations that do not offer promotion as an incentive (Tsui 2003). Therefore, gainsharing enables the organisation to recognise its employees’ creativity and intelligence in ways other than by increasing their rank or formal status. The organisational perspective of gainsharing is linked to organisational behaviour that plays a pivotal role in understanding employee behaviour (Wellbourne & Gomez-Mejia 2011). In this regard, employees must perceive that gainsharing is properly set up and that procedures are fair and objective. Snee and Hoerl (2003) suggest the factors that must be addressed when creating an effective framework for unbiased gainsharing programmes. This includes the utilisation of an easy-to-understand formula that tracks those variables that directly affect an organisation’s strategic performance and a regular programme evaluation (at least annually). This involves developing metrics to assess programme performance, creating procedures for revising the bonus formula and using a process for communicating the programme’s changes. It must clarify employee involvement during design, implementation and periodic evaluation. Organisations that solicit employee input regarding programme design tend to have programmes that outperform designed systems (Gardner 2011). Gainsharing is a base reward system that pays at a current market level. It is not a substitute for salaries below the market level (Wellbourne & Gomez-Mejia 2011). It is designed for and works best when augmenting a base salary system that reflects market conditions. The success of a system relies partly on the subject matter expected to guide the design process. In addition, the product or service line must be stable. Organisations that have relatively stable product or service lines, or an ability to develop a stable formula, tend to have the highest success rate.

In the USA, Brazil and parts of Europe, gainsharing creates a working environment that encourages worker participation and provides opportunity for linking improved performance to better compensation (Wellbourne & Gomez-Mejia 2011). According to Leitman et al. (2010) in the private health sector in the USA, a pay-for performance programme introduced at a large private hospital between July 2006 and June 2009 resulted in a $25 million reduction in costs. The gainsharing programme proved an incentive for medical staff to reduce hospital costs while maintaining quality care. At Ford Motor Company (in the USA), employees at dealerships are given purchasing incentives (Sachin & Roble 2008). If they can buy the part below the normal purchase price, they get a share of the overall savings that are made. The aforesaid findings bring important perspectives to the effectiveness of gainsharing in a global context.

The study is based on the following assumption:

H1: The implementation of a gainsharing programme leads to labour productivity improvement in the automotive parts manufacturing companies.

Ho: The implementation of a gainsharing programme does not lead to labour productivity improvement in the automotive parts manufacturing companies.

Having presented the main hypothesis for this study, Table 1 lists the study sub-hypothesis.

This study was quantitative in nature. Bryman and Bell (2007) explain that the quantitative approach involves the use of statistical procedures to analyse the data collected. Consequently, after the measurement of the relevant variables, the scores were transformed using statistical methods. The study was also conclusive in design. Conclusive studies are meant to provide information that is useful in reaching decision-making (Yin 2008).

The study is comparative in nature using quantitative research tools. A convenience sample utilising three large companies that are in the automotive parts industry situated within the eThekwini District Municipality in the Province of KwaZulu-Natal in SA was used. The two companies that adopted gainsharing as an incentive strategy agreed to participate in the study. They are identified as companies A and B. The third company, which adopted a 360-degree performance appraisal system, is identified as company C and is included in the study for comparative purposes. Company A had 1005 employees, whereas company B had 1300 employees, and both operate a three-shift system. Company C uses a 360-degree performance appraisal system and also operates a three-shift system. It is situated in the same municipal area and has 1400 employees.

The collection of data from two automotive parts manufacturing companies (A and B) was carried out in two phases. The first phase involved the collection of pre- and post-gainsharing results for spoilage, absenteeism, capital investment and labour productivity. The pre-gainsharing results were quarterly data reflecting each company’s performance over the 3 years prior to gainsharing implementation. This includes data from the first quarter of 2005 to the final quarter of 2007 (2005Q1–2007Q4). The post-gainsharing data reflect the company’s performance for the period of 3 years after the implementation of gainsharing. This involves data from 2008Q1 to 2010Q4. In the period between the 2011 and 2016, both companies A and B were involved in labour restructuring. This emanated from the strategic changes that took place in the motor assembly plant of the company they are supplying. Hence, the data from the restructuring period were excluded from the study. The next part of the study involved collecting pre- and post-quarterly data for spoilage, absenteeism, capital investment and labour productivity from the other automotive parts manufacturing company (C) that uses a 360-degree performance appraisal system. Company C’s data set ranges from 2004Q1 to 2009Q4. However, they adopted the 360-degree performance appraisal system in 2007Q1. The reason for including company C in the study was to compare gainsharing results with a different incentive system.

The company’s quarterly time series data on labour productivity, spoilage, absenteeism, number of workers involved in production and investment were used. Although companies A and B are relatively similar in nature, the researcher pooled the data from the two companies for an optimum sample size so that statistically valid results could be obtained. The measurements were based on 22 observations (after adjustments) per company. Therefore, the results are based on the total of 44 observations. Similarly, company C’s quarterly time series data on absenteeism, labour productivity and spoilage rates were used. The measurements were based on the total of 24 observations.

Additionally, a dummy variable that assumed the value of 0 and 1 to represent the pre- and post-gainsharing periods, respectively, was introduced into the ordinary least squares (OLS) model. The aim was to isolate the pre- and post-labour productivity effects. Consequently, if gainsharing proved to be a useful strategy in raising labour productivity levels, this would result in a statistically significant coefficient on the dummy variable.

Hence, the favourable findings regarding the co-integrating tests enabled the study to engage in quantitative analysis involving OLS in order to quantify the magnitude of the effectiveness that the implementation of gainsharing has had on labour productivity. Co-integration provides evidence of a long-run relationship between variables (Juselius 2006).

The OLS model used was as follows:

Labour productivity = Bo + B1 Spoilage + B2 Absenteeism + B3 Number of workers involved in production + B4 Investment + B5 Pre/Post-dummy

The above model assumes that labour productivity is a function of spoilage rate, absenteeism rate, the number of workers involved in production, investment and gainsharing strategy. The investment variable is the labour productivity lagged by 1 period (i.e. 1 quarter). This variable aims to capture previous machinery input (i.e. past capital investment).

For the study to achieve its objective, stationarity tests (as shown in Table 2) were conducted in order to determine the status of the variables.

The results for both companies’ (A and B) pooled data indicate that the variables exhibit mixed orders of integration. If one ran the OLS models that had non-co-integration level variables, this could have resulted in spurious regressions. As a result, the tests in Table 3 were carried out on the assumption that the co-integrating vector comprises the labour productivity, spoilage rate, absenteeism, number of workers and the exogenous policy dummy variables.

The above tests show that the variables of companies A and B have a co-integrating relationship. This reflects that there is more than one co-integrating relationship in the pooled data of companies A and B (also shown as AB) in Table 3. This indicates that the results in Tables 4 and 5 consist of statistically valid relationships that could represent long-run relationships. However, results for company C show that there are no co-integrating relationships between the variables under consideration. This implies that the related OLS regressions for company C in Tables 4 and 5 contain variables that do not have long-run relationships.

Table 4 presents the comparative results of labour productivity as a dependent variable to absenteeism and spoilage rates, the number of workers involved in production, as well as dummy variables (for gainsharing and 360-degree performance appraisal).

This section analyses data using factorial designs. It incorporates box plots to determine whether the factorial ANOVA assumptions of normality and homogeneity of variance have been met. Porkess (2005) explains that the populations represented should be normally distributed (i.e. the normality), making the mean an appropriate measure of central tendency. However, the homogeneity of variance indicates that the population from which the data are sampled should have the same variance. In this study, ‘policy 1’ is the pre-dummy period, whereas ‘policy 2’ is the post-dummy. Figure 1 represents the box plots for this study.

Figure 1 shows that there are similar spreads of D_mean for company A (labelled as company 1) and company B (labelled as company 2). Although the D_means are similar, the variances of company C (labelled as company 3) are much larger when compared to company A and company B. In all cases, the D_means for the three companies are normally distributed.

Figure 2 presents the estimated marginal means of D_means for companies A, B and C (labelled as 1, 2 and 3, respectively).

Figure 2 shows the interaction between the three companies. The interacting factors between the marginal means for company policy 1 (pre-dummy) and policy 2 (post-dummy) periods have yielded patterns of differences between the D_means. This means that policy interactions that took place between companies A and B are significant in relation to company C. The effect of marginal means of the policy variable at companies A and B is relatively different to the marginal means of company C. The mean difference is partly based on the fact that the method of operations, the product classification and policy types (i.e. gainsharing system) for companies A and B are almost similar to each other, whereas company C uses the 360-degree performance appraisal system. Thus, there are no mean changes for company C when comparing the mean changes for both companies (A and B) in relation to pre- and post-policy periods.

Therefore, the results indicate that the implementation of gainsharing improved labour productivity for companies A and B. In contrast, they indicate that the implementation of 360-degree performance appraisal does not improve labour productivity, as measured in company C. The results are confirmed by study analysis from sections ‘Labour productivity as a dependent variable to dummy variables’.