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Constructive deviance has received increasing attention across the last 20 years. However, because the distinction between constructive and traditional forms of deviance (i.e., destructive) is based on the intent behind the behaviors, it can be difficult to determine which acts are constructive. As an umbrella construct consisting of several forms of deviant acts (e.g., whistle-blowing, employee voice, necessary evils), research into constructive deviance has largely remained focused on the individual behaviors to date. While advancements have been made, this focus has limited the consideration of an overarching understanding of constructive deviance in the workplace. Further, constructs like constructive deviance that straddle the bounds between beneficial and detrimental necessitate the exploration into their antecedents as determined by the employees (i.e., apples), their environments (e.g., barrels), or some combination of the two. The author seeks to advance the research in constructive deviance by proposing a testable model. In which, the author develops an interactionist perspective of the antecedents to reposition constructive deviance as the acts of good employees in restrictive or negative environments. In doing so, the author considers how various aspects of individuals, their organizational environments, and the influence of their leaders interact. The author then develops a multi-stakeholder approach to the outcomes of constructive deviance to consider how the various parties (i.e., organization, coworkers, customers) are expected to respond and how these responses impact the more distal outcomes as well as the likelihood of engaging in future constructive deviance.

We studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.

We collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.

Our findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.

One limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.

Our findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.

This paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.

This paper aims to compare the nature of three different business and management education (BME) research streams (online/blended learning, entrepreneurship education and experiential learning), along with their citation sources to draw insights on their support and legitimacy bases, with lessons on improving such support and legitimacy for the streams and the wider BME research field.

The authors analyze the nature of three BME research streams and their citation sources through tests of differences across streams.

The three streams differ in research foci and approaches such as the use of managerial samples in experiential learning, quantitative studies in online/blended education and literature reviews in entrepreneurship education. They also differ in sources of legitimacy recognition and avenues for mobilization of support. The underlying literature development pattern of the experiential learning stream indicates a need for BME scholars to identify and build on each other’s work.

Identification of different research bases and key supporting literature in the different streams shows important core articles that are useful to build research in each stream.

Readers will understand the different research bases supporting the three research streams, along with their targeted audience and practice implications.

The discovery of different support bases for the three different streams helps identify the network of authors and relationships that have been built in each stream.

According to the authors’ knowledge, this paper is the first to uncover differences in nature and citation sources of the three continuously growing BME research streams with recommendations on ways to improve the support of the three streams.