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The objective of this study is to construct a theoretical framework concerning wage determination, grounded in principles and supplemented by conventional theories. It discusses the Islamic perspectives on minimum wage and examines contemporary challenges and intricacies in its application.

This study uses thematic analysis to create the conceptual framework, drawing upon a review of pertinent literature such as academic papers, books and articles published up to 2023.

The framework encompasses various categories, namely, employee characteristics, job characteristics, market factors, compensation practices and Islamic principles. Each category consists of multiple variables. The resulting framework offers a holistic and ethically grounded methodology for wage determination, aligning with both Islamic and conventional perspectives. This study notes the absence of a universally agreed-upon minimum wage. Islamic economics faces challenges due to the unclear application of principles, limited awareness, legal constraints and a lack of empirical evidence on wage systems, along with complexities in their implementation.

The paper’s limited scope focuses solely on the Islamic perspective on wage determination, without comparing it to the conventional viewpoint. This may have implications for future research.

The insights on Islamic principles and wage determination guide scholars and policymakers interested in promoting just and equitable wages.

This study is distinct in its integration of various factors to propose an all-encompassing framework for wage determination, rooted in the Quran and principles, while also reinforcing the framework with conventional theories. Additionally, it adds to the growing body of literature by investigating the Quran’s stance and principles on minimum wage, as well as discusses the challenges involved in implementing an Islamic approach to wage determination, which has received limited attention in Islamic literature.

In the most recent years, social, innovative, economic and political changes in the European context have characterized consumers' behaviours. The paper aims to understand if the use of electronic commerce differs in a situation characterized by uncertainty.

An innovative approach to categorising online consumer behaviour considers the self-determination theory and basic psychological needs in an uncertain scenario. The research is based on a quantitative analysis obtained by clustering algorithms on a sample of 1,000 digital users in European countries. A structured questionnaire was administered online and distributed through the leading online social platforms and direct mailing.

The results show online activities during changes in consumer behaviour patterns and retailers' strategies. This research will allow online retail managers and practitioners to obtain important information to help them define appropriate customer-oriented strategic actions to enhance value in the electronic context for both customers and firms.

The innovation of this research approaches the categorization of online consumer behaviour by exploiting the self-determination theory in an uncertain scenario. Precisely, the novelty of this research is to highlight three detailed categories of electronic commerce consumers, namely, unwilling, halfback and digital, to collect, store and disseminate information about these categories of Online Consumers Behaviours.

This study aims to investigate gamification-based training program through the lens of self-determination theory and in the context of corporate training programs. It integrates the self-determination theory, game elements and learning outcomes in gamified training programs to derive insights.

Data is sourced from software development companies operating in the city of Bangalore in India. It applies the partial least square structural equation modeling to investigate the relationship between the self-determination learning theory and game elements and the impact it has on learning outcomes.

As a precursor to the development of a game-like learning ecosystem, the authors study the perception of trainers and human resource managers toward game-based training programs in the organization. The authors find that game-based learning makes training more engaging, immersive and contextual for the learners.

The study is based on a specific sector, i.e. software development companies, and so the results may lack in generalizability. Future research, therefore, may consider other industrial sectors such as manufacturing, banking and telecom to understand the relationship between the constructs.

This study provides insights for the trainers, human resource managers and academicians on the effectiveness of gamification-based training programs. It also provides information on how the learning theory can be leveraged to understand gamification-based training programs.

This work fulfills an identified need of the training industry to understand new methods of training with an aim to improve the learning outcomes among the learners.

This study provides a deep understanding on the effectiveness of training tools such as gamified training programs in enhancing and improving the learning outcomes among the learners.

The purpose of this study was to explore intrinsic and extrinsic motivations that led 28 teachers of emergent bilingual (EB) students to seek a master's in educational administration with a focus on bilingual/English as a second language (ESL).

To address the study objectives, the authors used a qualitative phenomenological design. The authors conducted online interviews with 28 teachers of EBs. The authors used the self-determination theory as the theoretical framework.

Primarily, teachers of EBs were intrinsically motivated to seek the principalship. The authors identified additional motivators that were not found in the previous literature which heretofore was based on general education teachers' responses. Those motivators were, gain advice from mentors, promote cultural awareness, commit to a campus-wide impact, increase awareness of the importance of bilingual/ESL education programs, and foster a relationship with the school community.

Identifying the intrinsic and extrinsic motivators for teachers of EBs who desire to move into a principal position may aid faculty in university principal preparation programs and administrators in school districts to support and mentor these teachers to better serve as leaders in high need schools.

There is little known about intrinsic and extrinsic motivations of teachers of EBs which influence their decisions to change their career paths to become principals.

This study aims to apply new modifications by changing the nonlinear logarithmic calculation steps in the method based on the removal effects of criteria (MEREC) method. Geometric and harmonic mean from multiplicative functions is used for the modifications made while extracting the effects of the criteria on the overall performance one by one. Instead of the nonlinear logarithmic measure used in the MEREC method, it is desired to obtain results that are closer to the mean and have a lower standard deviation.

The MEREC method is based on the removal effects of the criteria on the overall performance. The method uses a logarithmic measure with a nonlinear function. MEREC-G using geometric mean and MEREC-H using harmonic mean are introduced in this study. The authors compared the MEREC method, its modifications and some other objective weight determination methods.

MEREC-G and MEREC-H variants, which are modifications of the MEREC method, are shown to be effective in determining the objective weights of the criteria. Findings of the MEREC-G and MEREC-H variants are more convenient, simpler, more reasonable, closer to the mean and have fewer deviations. It was determined that the MEREC-G variant gave more compatible findings with the entropy method.

Decision-making can occur at any time in any area of life. There are various criteria and alternatives for decision-making. In multi-criteria decision-making (MCDM) models, it is a very important distinction to determine the criteria weights for the selection/ranking of the alternatives. The MEREC method can be used to find more reasonable or average results than other weight determination methods such as entropy. It can be expected that the MEREC method will be more used in daily life problems and various areas.

Objective weight determination methods evaluate the weights of the criteria according to the scores of the determined alternatives. In this study, the MEREC method, which is an objective weight determination method, has been expanded. Although a nonlinear measurement model is used in the literature, the contribution was made in this study by using multiplicative functions. As an important originality, the authors demonstrated the effect of removing criteria in the MEREC method in a sensitivity analysis by actually removing the alternatives one by one from the model.

The purpose of this paper is to provide an outline of the major contributions in the literature on the determination of the least distance in data envelopment analysis (DEA). The focus herein is primarily on methodological developments. Specifically, attention is mainly paid to modeling aspects, computational features, the satisfaction of properties and duality. Finally, some promising avenues of future research on this topic are stated.

DEA is a methodology based on mathematical programming for the assessment of relative efficiency of a set of decision-making units (DMUs) that use several inputs to produce several outputs. DEA is classified in the literature as a non-parametric method because it does not assume a particular functional form for the underlying production function and presents, in this sense, some outstanding properties: the efficiency of firms may be evaluated independently on the market prices of the inputs used and outputs produced; it may be easily used with multiple inputs and outputs; a single score of efficiency for each assessed organization is obtained; this technique ranks organizations based on relative efficiency; and finally, it yields benchmarking information. DEA models provide both benchmarking information and efficiency scores for each of the evaluated units when it is applied to a dataset of observations and variables (inputs and outputs). Without a doubt, this benchmarking information gives DEA a distinct advantage over other efficiency methodologies, such as stochastic frontier analysis (SFA). Technical inefficiency is typically measured in DEA as the distance between the observed unit and a “benchmarking” target on the estimated piece-wise linear efficient frontier. The choice of this target is critical for assessing the potential performance of each DMU in the sample, as well as for providing information on how to increase its performance. However, traditional DEA models yield targets that are determined by the “furthest” efficient projection to the evaluated DMU. The projected point on the efficient frontier obtained as such may not be a representative projection for the judged unit, and consequently, some authors in the literature have suggested determining closest targets instead. The general argument behind this idea is that closer targets suggest directions of enhancement for the inputs and outputs of the inefficient units that may lead them to the efficiency with less effort. Indeed, authors like Aparicio et al. (2007) have shown, in an application on airlines, that it is possible to find substantial differences between the targets provided by applying the criterion used by the traditional DEA models, and those obtained when the criterion of closeness is utilized for determining projection points on the efficient frontier. The determination of closest targets is connected to the calculation of the least distance from the evaluated unit to the efficient frontier of the reference technology. In fact, the former is usually computed through solving mathematical programming models associated with minimizing some type of distance (e.g. Euclidean). In this particular respect, the main contribution in the literature is the paper by Briec (1998) on Hölder distance functions, where formally technical inefficiency to the “weakly” efficient frontier is defined through mathematical distances.

All the interesting features of the determination of closest targets from a benchmarking point of view have generated, in recent times, the increasing interest of researchers in the calculation of the least distance to evaluate technical inefficiency (Aparicio et al., 2014a). So, in this paper, we present a general classification of published contributions, mainly from a methodological perspective, and additionally, we indicate avenues for further research on this topic. The approaches that we cite in this paper differ in the way that the idea of similarity is made operative. Similarity is, in this sense, implemented as the closeness between the values of the inputs and/or outputs of the assessed units and those of the obtained projections on the frontier of the reference production possibility set. Similarity may be measured through multiple distances and efficiency measures. In turn, the aim is to globally minimize DEA model slacks to determine the closest efficient targets. However, as we will show later in the text, minimizing a mathematical distance in DEA is not an easy task, as it is equivalent to minimizing the distance to the complement of a polyhedral set, which is not a convex set. This complexity will justify the existence of different alternatives for solving these types of models.

As we are aware, this is the first survey in this topic.

South Africa’s wool industry plays an important role in the agricultural sector. The wool industry provides a valuable source of income for farmers who practice sustainable farming practices. However, wool farmers face numerous challenges, such as wool contamination, dirty wool and producing good-quality wool. Good-quality wool is determined by fibre diameter, clean yield, vegetable matter and staple length. This study aims to address these challenges.

A multiple regression analysis of price (R/kg) of White wool and Merino wool was applied to four variables fibre diameter: vegetable matter, clean yield and staple length. The analysis was based on the data for the 2009–2019 data from Cape Wools auctions.

Fibre diameter, clean yield and staple length, with exception of vegetable matter, made a statistically significant contribution to the determination of wool price after all other independent variables were controlled for (p < 0.05). A one-unit (micron) increase in fibre diameter resulted in a 0.404-unit decrease in wool price (R/kg). A one-unit (mm) increase in staple length resulted in a 0.022-unit increase in wool price (R/kg). There was no statistically significant association between vegetable matter and wool price. A one-unit increase in clean yield was associated with a 0.111-unit increase in wool price (R/kg).

Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool.

Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool.

In a developing country such as South Africa, this study is important for the following reason. It is understanding the wool characteristics that have the most significance influence on the determination of wool price for Merino wool and White wool might effectively help the wool farmers to adapt their production systems to improve the wool characteristics that determine wool price.

This study identified a need for a study to be conducted on all wool classes.

By studying Annie Besant’s leadership style as a transformational leader, women can learn how to effectively lead and empower themselves and others in their pursuits.

This qualitative study explores the potential of Annie Besant’s personality traits and leadership style to derive a model for sustainable women’s empowerment.

This study provides valuable insights into a potential framework for sustainable women empowerment based on Annie Besant’s personality traits and proposes a sustainable women empowerment model.

This is a theoretical model represented in a graphical mode, the societal impact of the model is yet to be ascertained.

This article is an original concept inspired by the life of Annie Besant, an Irish woman of many virtues.

Building on the self-determination theory (SDT), the purpose of this study is to empirically examine the influence of work meaningfulness (WM) on employees' involvement in playful work design (PWD) in the context of software development firms in Pakistan.

For the present study, a two-wave employee survey (online questionnaire) was used for data collection. The data were collected through an adopted questionnaire from employees working in software development firms in Pakistan. structural equation modeling and Hayes Process Macro of SPSS were used to analyze data collected from 305 respondents.

The findings of this study show that work meaningfulness and epistemic curiosity (EC) positively and significantly influence employee playful work design strategies. Moreover, the relationship between work meaningfulness and playful work design was partially mediated by employee epistemic curiosity. This mediating role of epistemic curiosity is strengthened by the presence of the perceived leader's autonomous support (LAS).

Employees improve their personal work experience through playful work design. Theoretically, this study contributes to the body of knowledge on the factors (work meaningfulness, epistemic curiosity and leader's autonomous support) that can influence employees' self-determination to design fun and competition into their work. This study contributes to the theory by introducing the antecedents (work meaningfulness and epistemic curiosity), of employee playful work design and explores the role of epistemic curiosity as a mediator and the leader's autonomous support as a moderator through SDT perspective.

For practitioners, this study pinpoints that software development firms can consider improving employees' perception of work meaningfulness, which can lead them to become epistemically curious to proactively design their work experience for their psychological need fulfillment, well-being and better functioning. Moreover, leader's autonomous support can support involvement in playful work design.

The current study is the first investigation in the Asian context to study the antecedents of playful work design and a critical boundary condition. This study extends the literature on the antecedents of employee playful work design and explores the role of epistemic curiosity as a mediator and the leader's autonomous support as a moderator specifically through a self-determination perspective.

This study aims to identify the counterproductive knowledge behavior (CKB) of volunteers in nonprofit organizations and its influencing factors, based on the theories of planned behavior and well-being.

An online survey was used to collect 496 valid responses. A structural equation model was constructed, and the relationships among the constructs were estimated via the maximum likelihood method. To analyze the direct and indirect effects, 2,000 bootstrapping runs were conducted. A Kruskal-Wallis test was also conducted to analyze the relationship between the variables.

A combination of organizational factors and individual attitudes and perceptions can be used to explain CKB. Insecurity about knowledge sharing had the greatest impact on CKB. A competitive organizational norm induced CKB while a knowledge-sharing organizational norm did not have a significant impact. Further, the more self-determined the volunteer activity was, the more the CKB was suppressed. However, well-being did not have a significant direct effect. Volunteers with high levels of well-being and self-determination had significantly lower levels of insecurity about knowledge sharing compared to those who did not.

Well-being arising from volunteering did not directly suppress CKB. To improve organizational efficiency by reducing CKB, nonprofit organization managers should provide intrinsically motivating tasks and interact with the volunteers.

There is a lack of empirical research on CKB in volunteer organizations; therefore, the authors propose a new approach to knowledge management in volunteer activities.