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Existing literature on algorithmic management practices – defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice and – as a result – workplace well-being. Literature review revealed a significant gap in empirical research on the nature and direction of these relationships. Therefore the purpose of this paper is to analyse how algorithmic management practices directly influence workplace well-being, as well as investigating its relationships with job autonomy and total rewards practices.

Conceptual model of relationships between algorithmic management practices, job autonomy, total rewards and workplace well-being has been formulated on the basis of literature review. Proposed model has been empirically verified through confirmatory analysis by means of structural equation modelling (SEM CFA) on a sample of 21,869 European organisations, using data collected by Eurofound and Cedefop in 2019, with the focus of investigating the direct and indirect influence of algorithmic management practices on workplace well-being.

This research confirmed a moderate, direct impact of application of algorithmic management practices on workplace well-being. More importantly the authors found out that this approach has an indirect influence, through negative impact on job autonomy and total rewards practices. The authors observed significant variation in the level of influence depending on the size of the organisation, with the decreasing impacts of algorithmic management on well-being and job autonomy for larger entities.

While the influence of algorithmic management on various workplace practices and effects is now widely discussed, the empirical evidence – especially for traditional work contexts, not only gig economy – is highly limited. The study fills this gap and suggests that algorithmic management – understood as an automated decision-making vehicle – might not always lead to better, well-being focused, people management in organisations. Academic studies and practical applications need to account for possible negative consequences of algorithmic management for the workplace well-being, by better reflecting complex nature of relationships between these variables.

This study is carried out to evaluate how well legal knowledge can be demonstrated by a built environment professional via the scenario-based approach to the learning of law modules.

A Delphi analysis of the advice provided by an MSC quantity surveying student, on a scenario-based legal problem arising due to a property contract, is carried out. The tendered legal advice was submitted as part of the assessment requirements for an MSc law module, following the university criteria, after the teaching of a law module. The student report, which attained an A-grade, and the assessment criteria used for marking/grading by the university were subsequently sent to 18 practicing lawyers, who were selected to constitute an expert panel, to independently judge the extent of legal knowledge demonstrated in the student report.

The Delphi analysis outcome showed that the expert panel holds a similar consensus view to the university on the level of legal knowledge demonstrated and by extension the effectiveness of the law module in imparting legal knowledge to a non-lawyer. The study outcome shows how well legal knowledge can be acquired and applied by a non-lawyer, within the context of the built environment, via scenario-based teaching of a law module.

This study serves as a preliminary step necessary to arouse further research toward empirically profiling the current outlook of a wider range of graduating students receiving scenario-based legal education in the built environment.

This study investigates determinant factors (influence of the third party (ITP), credit policy (CP) and follow-up process (FP)) of micro, small and medium enterprises' (MSMEs) accounting processes (APs) and strategic debtors' management.

The study employed a sequential mixed-method approach, combining quantitative and qualitative methods for comprehensive data analysis. Phase I involved purposively selecting and interviewing 10 MSME owners or accountants to gain insights into debtors' management. In Phase II, a quantitative approach was used for collecting survey data from 72 MSME owners or accountants. Structural equation modeling-partial least squares (SEM-PLS) are the statistical tools that validated the study's proposed hypotheses.

The findings indicate that determinant factors (ITP, CP and FP) positively affect MSMEs' AP, significantly influencing strategic debtors' management. As a result, sole proprietors can use this study's findings to create value through systematic management of their debtors, guaranteeing sustainable firm growth and profitability.

The sample has restricted to MSMEs in Oman, where the findings may not be generalized to other companies. Overall, the findings suggest that it requires considering the proposed determinant factor of MSMEs' AP to manage their debtors or accounts receivable (AR) to be more profitable.

MSMEs play an essential role in the growth of any country's economy. However, the dearth of comprehensive research on influential factors of MSMEs' debtors’ management studies justifies the significance of the current study.

This paper aims to examine the relationship between the implementation of soft lean practices and organizational resilience development in the service sector.

A mixed-methods explanatory design that relied on two sequential and complementary phases was adopted. In the first phase, a quantitative analysis was performed based on data collected from practitioners from service organizations, allowing the identification of the significance of this relationship. In the second phase, the authors used semi-structured interviews with experts to qualitatively assess how this relationship occurs.

Findings indicated that soft lean practices are positively associated with organizational resilience, although the extent of their relationships varies depending on the resilience ability under analysis. Interviews with experts also provided specific details on how such relationships occur, adding insights to the numerical results.

This study provides a deeper understanding of the implications of lean management, specifically concerning the support of soft lean practices to develop organizational resilience. Additionally, the identification of this relationship (and how it occurs) allows service organizations to deploy human-related strategies to promote broader adoption of certain soft lean practices. As socio-cultural changes are usually time-consuming, anticipating these organizational resilience needs may result in competitive advantages in the face of disruptive events.

This paper contributes insights into how different firm types in the emerging market (EM) of Turkey respond to upgrading pressures in terms of internationalization and the usage of domestic political support. It seeks to highlight how the usage of and the responses to different strategies, connections and policy instruments vary with firm types.

Binary logistic regression analysis is used to differentiate and identify characteristics of firms regarding market-seeking strategies and their usage of institutional and financial support. The analysis is based on survey data from firms located in the metro-region of Istanbul: advanced market multinational enterprises (AMNEs), Turkish MNEs (TMNEs) and domestic Turkish firms (DTFs).

Different types of firms within the population of innovative firms in the EM setting of Turkey show significant variety regarding the usage of and the responses to key factors affecting internationalization. AMNEs particularly benefit from investment and export incentives as well as from establishing political connections in Turkey. DTFs significantly use tax incentives and primarily seek advanced markets. TMNEs particularly benefit from investment and export incentives and prefer to target advanced markets.

Using Turkey as a single-country setting is a limitation to the generalizability of the results. Future studies could use more cases of AMNEs to compare different countries of origin. In addition, the intended focus on R&D-related firms produces specific outcomes for such companies.

National and regional policies need to pursue different strategies for the surveyed groups of firms to attract and maintain foreign direct investments (FDIs) of AMNEs as well as to support outward FDIs of domestic firms and EM MNEs. In particular, policies for market entries and knowledge sourcing in advanced markets are becoming a crucial factor for EM firms in overcoming a shortage of resources at home.

This paper’s findings challenge existing theories such as the concept of psychic distance or liabilities of foreignness, which do not always provide an adequate explanation for internationalization activities of EM firms. In addition, it is highly relevant to apply an eclectic or multidimensional concept when conducting research in EMs in order to capture the interrelated constructs of upgrading, internationalization and political support.

This study aimed at determining factors which affect university lecturers’ adoption of the Moodle platform under the conditions of COVID-19. In considering the condition of the COVID-19 pandemic, the unified theory of acceptance and use of technology (UTAUT) model was applied and extended by adding two additional variables of learning demand and time pressure to assess their influence on Moodle platform adoption.

Data were obtained from the 226 participants through an online structured questionnaire. The covariance-based approach of structural equation modeling was used to examine the proposed model. The structural model was tested using the maximum likelihood method of analysis of a moment structures to analyze the study’s hypotheses.

Results suggest that performance expectations have a substantial influence on behavioral intent. The effort expectancy, social effect and facilitative factors have no effects on behavioral intentions. Facilitating conditions directly and significantly affect the actual use of Moodle. The results also reveal that learning demands, which is a salient predictor of perceived time pressure, in turn directly and significantly affects the actual use of Moodle. Finally, the behavioral intention has a strong influence on Moodle’s actual usage.

Although the UTAUT 2 model is considered to be a new and updated version of UTAUT, it has not been used since newly added variables, namely, price, habit and hedonic motivations, are less related to the context and to avoid respondents’ paradox. Moreover, using the Moodle platform in the researched context is compulsory for both students and instructors. Discussion, insights, limitations and recommendations for future studies are suggested.