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This study aims to identify key research clusters (or sub-fields) in the field of performance measurement research, analyse its historical development and propose future research avenues.

Several bibliometric analysis methods, including co-citation analysis and text mining techniques, were used to review papers published on performance measurement research.

This study reveals eight main clusters of research in this field, ranging from theoretical-focused clusters (e.g. strategic performance measurement) to practical-focused clusters (e.g. design of performance measurement). These clusters are further categorised into four groups based on the size and degree of connectedness. Regarding the analysis of historical development, the established clusters, such as supply chain management, remain important, while newer clusters, such as hospitality and humanitarianism, have recently gained increasing interest.

This study applies citation-based clustering, a type of bibliometric literature review method that has been underused in the field of performance measurement. Moreover, the results obtained from this study are also distinct from those of previous studies, offering valuable insights especially for researchers. With a comprehensive understanding of the field, researchers can use it to understand the key literature, observe ongoing developments within their specialisation and inform their future research directions.

This study aims to analyze the effects of socialization mechanisms (belief system and peer mentoring) on managers’ job engagement and their desire to have a significant impact through work, that is, the desire to substantially improve or facilitate the lives of others by performing their work. The study also examines the moderating role of organizational identification.

A survey was conducted with middle and lower-level managers at one of the largest banks in Brazil, the BankCo. The authors obtained a sample of 201 respondents and tested the research hypotheses with structural equation modeling. The authors also performed a complementary data analysis with fuzzy-set qualitative comparative analysis.

The results suggest that belief systems and peer mentoring directly promote job engagement and indirectly promote desire to have a significant impact to a better world through work (through full mediation of job engagement). The effects of job engagement on desire to have a significant impact through work are even greater when managers have high organizational identification. Finally, several causal combinations are sufficient for high levels of desire to have a significant impact through work.

Beyond studies that examine how organizational mechanisms influence employee outcomes (e.g. performance), this study explores how socialization mechanisms can promote desire to have a significant impact through work. Thus, the authors demonstrate how organizational core values, mission statement and peer mentoring collaborate for managers to develop altruistic behavior, that is, directly related to other human values, such as empathy and ethics, being able to contribute to a world better.

This study developed and empirically tested a model that connects socialization mechanisms, job engagement, organizational identification and managers’ desire to have a significant impact through their work. Therefore, the paper provides insights into the relevance of socialization mechanisms for orchestrating managers’ proactive and altruistic behaviors.

Brand reputation (BR) is one of the most important factors that affect the consumer–brand relationship and give businesses a competitive advantage. Businesses with a strong BR can increase their market shares and product market prices, in addition to gaining a competitive advantage. In order for businesses to have these advantages, they need to know and analyze their consumers. This study aimed to develop an alternative analysis method by using classification algorithms and regression analysis to measure and evaluate the effect of consumers' BR perceptions on their willingness to pay premium prices (WPP).

The research data were collected from 483 participants by the online survey method due to the COVID-19 pandemic. The data were first analyzed with regression analysis, and the effect of BR on WPP was found to be significant. Then, using artificial intelligence (AI) methods that were not used in previous studies, consumers' perceptions of BR and WPP were clustered and classified.

The results revealed the highest and lowest customer groups with BR and WPP and empirically demonstrated that highly accurate practical classification models can be applied to determine strategies in line with these findings.

The model proposed in this study offers an integrated approach by using AI and regression analysis together and tries to fill the gap in the literature in this field. Therefore, the novelty of this study is to quantitatively reveal and evaluate the relationship between BR and WPP by using AI classification algorithms and regression analysis together.

Architectural programming, as a critical phase in construction projects, has been widely recognized for its importance and advantages throughout the construction process. With the rapid development of the socioeconomic landscape, architectural programming has garnered increasing attention from various other disciplines, becoming a key trend in interdisciplinary collaboration. This study aims to provide a comprehensive understanding of the current status and future directions of architectural programming from an interdisciplinary perspective through scientometric analysis and systematic review.

This study first collected English journal articles on architectural programming published between 1975 and 2024 from the Web of Science and Scopus databases. After an initial screening of titles and abstracts, 515 articles were selected for scientometric analysis to reveal the current state and advantages of architectural programming research in multidisciplinary fields. Subsequently, a second screening of full-text articles identified 75 journal articles for systematic review, focusing on research topics and challenges in interdisciplinary applications.

The study reveals an exponential increase in the number of papers related to architectural programming between 1975 and 2024, particularly in the last decade. Six key research topics of architectural programming in multidisciplinary fields were identified: (1) performance optimization and evaluation, (2) digitalization and automation development, (3) project management and decision support, (4) improvement of human and social welfare, (5) sustainable resources and environment and (6) educational practices of architectural programming. Additionally, the study identified the main challenges in the interdisciplinary application of architectural programming, including (1) incompatibility among disciplines, (2) limitations of data and methodologies and (3) insufficient social engagement. To address these challenges, three potential future directions were proposed: (1) establishing interdisciplinary teams and platforms, (2) enhancing multi-source data integration and digital transformation and (3) improving governance mechanisms and educational training.

By combining quantitative and qualitative methods, this study provides a comprehensive review of architectural programming research and applications in multidisciplinary fields, offering theoretical foundations and practical references for the future development of architectural programming. This review not only aids in understanding the overall status of current architectural programming research but also offers valuable insights and recommendations for future research directions and practical applications.

The study investigates the impact of the interaction effect of product market competition and rollover risk on the default risk of the firms.

The study used the sample of unbalanced panel data from Indian corporates without any survivability bias over the period from 2009 to 2020 consisting of 30,396 firm-year observations of 6,718 firms spread across 143 industry groups. The panel data regression tests the interaction effect in the context of the asset substitution problem, predation threat theory, competitive shock, and competitive risk.

The empirical results highlighted the dominance of the predatory effect of competition over the disciplinary advantage of short-term debts. The competitive shock to the industry results in a higher credit spread for refinancing short-term debt and significantly increases rollover risk for firms. Smaller firms have higher default risk from rollover losses than larger firms in the face of competition due to asset-substitution problems and strong rivalry. For firms with weaker fundamentals, the interaction effect of rollover risk and competition exacerbates the flight-to-quality problem, resulting in a systemic event.

The investors can benefit by factoring ex-ante the interdependence of competition, debt market illiquidity, and default premia while calculating the credit risk. The shareholders of competitive firms can reduce the moral hazard of refinancing the rollover losses and defaulting at a higher fundamental default threshold, by reducing sub-optimal utilization of funds by managers and agency costs.

As per the best of author knowledge, the present study is the first to study the moderating effect of product market competition in exacerbating default risk through the rollover channel.

Digital platforms that offer on-demand gig work, while providing work opportunities in the economy, have raised social and economic concerns. Though extensive research on regulation of the gig economy exists, the effect of economic regulations on the welfare of the workers is not well understood. In this work, this paper aims to specifically study the effect of minimum wage and leisure regulations on the unemployment rate and offered wages. This paper also analyses the effect of up-skilling of the workers on unemployment and wages.

This paper builds an agent-based model of the labour market with heterogeneous workers and online platform firms that interact to match supply and demand. This paper also interviewed online workers in the two under-studied markets in online beauty and house maintenance services in India and included salient observations in to the model. This paper further validates the model findings with the interview observations.

Extensive simulations of the model indicate that the regulator's intervention on minimum wage and leisure reduces unemployment and offers better wages/leisure in the short term. However, these cannot be sustained unless the workers upgrade their skills, thereby improving their value to the employers. This paper also corroborates the authors’ interview observations on platforms deviating on stated worker contracts by simulating the same in the model. This paper finds that when platforms deviate on their stated incentive schemes, the unemployment rate tends to increase. This paper also finds that the emergence of online platforms in an erstwhile off-line market decreases the average unemployment rate with a moderate increase in the offered wage and leisure.

In this work, the focus has been to determine the worker-platform dyadic relationship. However, this is affected by consumer-related attributes such as ratings and associated reputation systems to promote trust between different stakeholders. Examining such a triadic relationship between consumers, platform and workers is required to comprehensively address the challenges of online gig economy.

Skilling and training are critical for worker mobility across tasks and jobs, especially in the gig economy. Gig workers, in general, seek to improve their skill level through self- or platform-enabled training programmes. The workers are able to generate more revenue through the new skills and hence can improve their reservation wage as well. This in turn increases average offered wages and reduces the overall unemployment in the sector. Despite attempts to classify gig workers as formal workers by labour laws across countries, there is resistance from online platforms. This is due to increased liability and responsibility that the platforms have to incur that possible increase their costs and expenses. This study shows that regulations, such as minimum leisure or minimum wage, increase the average wage or leisure in the market and increase unemployment. However, this might be a short-term phenomenon. In the long term, the gig workers benefit by enhancing their skills to not only stay employed but also bargain for better wages and leisure. The governments can play a larger role by facilitating upskilling programmes for the gig workers.

An extensive literature survey indicates that while most of the work on gig economy regulation emphasises the social and legal aspects, this work is unique in modeling the techno-economics of gig work. Further, while most of the economic research on gig work, focuses on consumers, this work focuses on the under-researched area of worker welfare. This paper also validates the model results with findings from the interviews with gig workers.

Mobile health (mHealth) technologies, in particular, have been sought after and advocated as a means of dealing with the pandemic situation. Despite the obvious advantages of mHealth, which include monitoring and exchanging health information via mobile applications, mHealth adoption has yet to take off exponentially. Expanding on the unified theory of acceptance and use of technology (UTAUT) model, this study aims to better comprehend consumers’ receptivity to mHealth even after the pandemic has subsided.

Through purposive sampling, data were collected from a sample of 345 mobile phone users and analysed using partial least squares structural equation modelling (PLS-SEM) and artificial neural networks (ANN) capture both linear and nonlinear relationships.

Effort expectancy, performance expectancy, social influence, pandemic fear and trustworthiness positively influenced mHealth adoption intention, with the model demonstrating high predictive power from both the PLSpredict and ANN assessments.

The importance–performance map analysis (IPMA) results showed that social influence had great importance for mHealth uptake, but demonstrated low performance.

Referrals are an alternative that policymakers and mHealth service providers should think about to increase uptake. Overall, this study provides theoretical and practical insights that contribute to the advancement of digital healthcare, aligning with the pursuit of Sustainable Development Goal 3 (SDG 3) (good health and well-being).

This study has clarified both linear and nonlinear relationships among the factors influencing intentions to adopt mHealth. The findings from both PLS and ANN were juxtaposed, demonstrating consistent findings.

This paper aims to present the vertical integration state-of-the-art and propose an expansion of the operations and supply chain management (OSCM) field by identifying gaps and bottlenecks.

This paper uses a systematic literature review based on a sample of 173 OSCM field articles, collected from Scopus and Web of Science databases.

There are no single factors, such as future costs, structures or skills development, in the decision to vertically integrate operations. It is necessary to combine the vision of production costs with the perspective of governance and transaction costs. In addition, it is essential to consider the competency perspective and its impact on capability building.

Few studies have attempted to understand how vertical integration is used in terms of OSCM research themes and theories. Vertical integration can help companies face challenges and serve as a potential solution for achieving better prices, demand control and quality management.

The significant role of vertical integration mechanisms in supply chains is crucial for managers evaluating a firm's reconfiguration with more vertical operations. Policymakers interested in supporting the smoothness of vertical integration decisions in regulatory agencies play a key role as contingencies.

In times of global challenges, vertical integration is a strategy known to be more effective for firms to obtain a competitive advantage, making them more resilient.

This paper addresses gaps in the vertical integration theme and provides insights for future research development.

This study aims to explore the impact of architecture on digital communication mediums, focusing on how social media shapes the public perception and discussion of architectural spaces. It specifically examines the case of the Basilica Cistern/Istanbul, analysing social media interactions post-restoration.

Using newspaper archive scanning and survey technique, this study observed public content on Instagram focusing on the post-restoration period of the Basilica Cistern. 406 (283 valid) people who visited the Cistern and shared their experiences on Instagram between August 2022 and January 2023 participated in a survey. The analysis utilized Python for advanced correlation studies, enabling an in-depth exploration of the interplay between architectural features and social media sharing behaviours.

The analysis revealed that historical significance, lighting elements, role as a photographic backdrop significantly influenced sharing behaviours. Correlations were found between specific spatial features of the cistern and various sharing motivations, such as communication with people, personal gain, and popularity. The study highlights a diverse spectrum of motivations among users, emphasizing the relationship between these motivations and spatial features.

This study underscores the necessity for further inquiry into the intricate dynamics among digital communication, architectural spaces, and user motivations. Limitations include potential challenges in gathering data from social media due to concerns of cyber fraud and the misuse of hashtags.

This research offers novel insights into the interplay between digital communication and architecture. It underscores the potential of digital platforms as valuable data sources for architectural theorizing and practice, particularly in understanding how restorations and architectural changes are perceived and discussed in the digital space.

The paper aims to examine Indonesian accounting students’ intention to become sustainable accountants (ISAs) using a modified theory of reasoning action model.

Primary data were collected from 239 respondents from five reputable universities in Semarang, Indonesia, using a structured questionnaire. A random sampling technique was employed and used in selecting respondents. The data were then analyzed using smart PLS (version 3.2.9) to obtain the final results.

The results show university sustainability (US) and attitudes toward sustainability (ATS) affect students' intentions to become ISAs. Knowledge has no direct correlation with students' intention to become ISAs. Path analysis shows a significant correlation between US and students' knowledge, attitudes and intentions regarding sustainability.

This is different from previous studies, which only focused on factors influencing students' intentions to pay attention to sustainability. This study focuses on prospective accountants because, in the future, they will be the technical executors of reporting using path analysis. This study further analyzes the relationship between existing antecedent variables. The results show that sustainability at the university is a variable that can influence all other variables.