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Due to the current shortage of skilled employees, there is a growing need to cope with given team settings and to offer appropriate team training. For team training, it is important to know how different competences influence team performance. Therefore, this study aims to examine the influence of social and cognitive competences on team performance and the relationship of the different competence dimensions to each other.

Data of 53 student and work teams was collected through a digital simulation laboratory, designed as an escape game. Competences of 228 team members were assessed through questionnaires prior to the simulation. Team performance was measured through short-term performance indicators. Additionally, a postsimulation survey regarding a long-term performance indicator was carried out. Three multiple regression analyses and mediation analyses were conducted.

A tradeoff between cognitive and social competences regarding their impact on short- and long-term team performance is observed. Facets of cognitive competences enhanced short-term performance, whereas facets of social competences reduced short-term performance while enhancing long-term performance. Although cognitive competences show a positive direct effect on short term performance, a negative indirect effect, mediated by social competences, became apparent.

This paper contributes to harmonizing contradictory findings on the impact of high achievers in teams. Although they can have an impact on rapid problem solving, long-term performance depends more on facets of social competences than cognitive competences. Furthermore, social and cognitive competences are positively correlated, showing that teams with higher cognitive competences tend to become stronger in terms of their social competences over time.

This study discusses the sources of value co-creation and its effects on businesses using social platforms such as Facebook, Instagram, Twitter and blogs.

A total of 301 survey responses were selected. The selected respondents indicated that they lived in South Korea, had an occupation as a private business or marketer and had used a social platform one or more times a day. The hypotheses were tested using a structural equation model.

The study reveals that the source of sustainable value co-creation between social platforms and businesses positively affects the competitive advantage of maintaining businesses. This advantage reveals an integrated relationship that leads to the successful financial performance of businesses through online word of mouth and customer satisfaction. Moreover, this study finds that the relationship between variables differs by social platform types (unidirectional vs bidirectional service).

The results of this study explain the relationship between value co-production, value-in-use, SCA and long-term performance. However, this study focused on private business and marketing staff working in companies in South Korea. Accordingly, more countries in which social platforms are widely utilized should be taken into account to help generalize the empirical findings.

There is a difference in the relationship between co-creation activity and cost advantage/long-term performance in accordance with the service type of a social platform. The results indicate that a bidirectional service is a more powerful tool for cost advantage and long-term performance.

This study focuses on the role of value co-creation in social platforms to ensure companies’ sustainable competitive advantage and performance. The results of this study will help companies develop online marketing strategies using social platforms.

Notwithstanding its significance as a form of strategic human capital investment, employee training has not yielded consistent conclusions among scholars regarding its impact on organizational performance. Some studies deem it effective, while others regard it as ineffective. We contend that distinct types of training impact various facets of firm performance.

In this study, we categorize employee training as either exploitative or explorative. Specifically, we examine their impact on two aspects of organizational performance: short-term performance and long-term competence, using a quasi-experimental setting and a difference-in-differences (DID) method.

We find that exploitative training is more effective in improving firms’ short-term performance (e.g. firms’ sales revenue), while explorative training is more effective in enhancing firms’ long-term competence (e.g. firms’ innovation output).

The findings of this study illuminate concrete benefits of training for practitioners, suggesting that firms can strategically select employee training category to maximize returns on their investment in strategic human capital based on their strategic orientations.

This study aims to investigate the impact of green marketing strategy (GMS) and firms’ decision to invest in or divest from green marketing activities during a crisis on business performance.

The study collected survey data from 245 Greek firms during the 2015 Eurozone crisis to investigate the impact of GMS and green marketing investments on firm resilience during crisis. Time-lagged, objective performance data for a subset of these firms helped examine the impact of GMS on postcrisis financial performance.

Pursuing a GMS builds resilience, especially for companies that decided not to reduce resources allocated to green marketing activities during a recession. Beyond resilience, firms investing in GMS during the crisis experienced improved financial performance in the long run. Finally, this research proposes a typology of GMS responses during a crisis.

This study does not specify which types of green marketing activities lead to more investment or divestment during a crisis.

The study offers insights for allocating resources to green marketing during recessions. Supporting GMSs during unpredictable times is important to successfully navigate performance both during and after a crisis. Six crisis response profiles are offered: green-nonbelievers, dis-investors, reluctants and cautious-, opportunistic- and strategic-green investors.

The study proposes a balanced approach to environmental sustainability, marketing strategy and firm performance during a crisis.

The study argues that GMSs enable firms to survive a crisis and recover from financial shocks.

This paper aims to propose an accurate and efficient decision-making process adapted to the specific context of Claim Management situations, implying partners engaged in a high-involvement relationship.

We used a three-step approach: first, an inductive phase based on 12 past case studies. Second, a theory-building phase. Third, a theory-testing phase based on an ongoing case study to observe and test our propositions.

Proposal 1: Partner’s Strategic Value is an influential decision parameter that must be incorporated into Claim Management-related decision-making processes in high-involvement relationships. Proposal 2: The Fast-and-Frugal Heuristic is adapted to the intense, interactive and iterative nature of the Claim Management context. Our final proposal combines these two findings, i.e. a Fast-and-Frugal Heuristic incorporating the Partner’s Strategic Value and based on using decision criteria as a sequence, not simultaneously.

In the context of high-involvement business relationships and Claim Management, this study introduces the importance of selecting an appropriate decision methodology and integrating a strategic decision parameter (Partner’s Strategic Value) into an operational decision-making context. Furthermore, the principle of considering decision parameters in a specific sequence corresponds to the iterative and interactive nature of the Claim Management processes.

This study investigates how environmental, social, and governance (ESG) factors influence intangible asset and intellectual capital valuation within the food and beverage (F&B) industry. By examining and contrasting global and European contexts, the research highlights ESG’s critical role in shaping the economic dimensions of sustainability across different regulatory environments. The results provide essential insights for stakeholders aiming to enhance corporate value through responsible business practices.

We adopt a quantitative fixed-effects panel regression analysis for ESG performance and intangible asset and intellectual capital values. The correlations between these variables are explored both globally and in the European Union using 1,034 observations from 502 F&B companies.

Globally, higher ESG performance corresponds to lower intangible asset values, a trend not observed in the European Union. Further, high ESG performance is associated with a decrease in intellectual capital value, suggesting that internal organisational efforts in this area should be rewarded in terms of short-term value.

This study provides a new understanding of the relationship between ESG performance, intellectual capital, and the F&B industry operating environment, highlighting the complexity and challenges associated with integrating ESG practices.

This study investigates the motivations and consequences of classification shifting from cost of sales to research and development (R&D) in high-technology industries.

This study conducts a multivariate analysis using logistic and ordinary least squares regression methods on panel data of high-technology firms for the period 1988–2012 to examine the effect of R&D classification shifting on gross margin benchmarks and future performance.

The results show that R&D classification shifting increases the likelihood of meeting or beating gross margin benchmarks. They also show that firms engaged in R&D classification shifting exhibit lower future R&D productivity, stock returns, and operating performance. The findings indicate that the short-term benefits of achieving gross margin benchmarks are offset by the long-term negative impact of R&D misclassification.

This paper provides insights that can help regulators develop clearer guidelines for the appropriate classification of R&D costs.

Moving beyond the core earnings management paradigm, this study demonstrates the use of R&D classification shifting as a tool to manipulate gross profits and R&D in high-technology industries. Most prior studies focused on the determinants of R&D classification shifting, while few investigated the impact of the practice. The findings in this study provide initial evidence of the consequences of R&D classification shifting for future R&D productivity and firm performance in high-tech industries. Using five methods, this study also validates R&D classification shifting and addresses the alternative explanation of R&D overinvestment.

Given the growing emphasis among scholars, practitioners and policymakers on financial sustainability, this study aims to explore the applicability of machine learning techniques in predicting the financial performance of microfinance institutions (MFIs).

This study gathered 9,059 firm-year observations spanning from 2003 to 2018 from the World Bank's Mix Market database. To predict the financial performance of MFIs, the authors applied a range of machine learning regression approaches to both training and testing data sets. These included linear regression, partial least squares, linear regression with stepwise selection, elastic net, random forest, quantile random forest, Bayesian ridge regression, K-Nearest Neighbors and support vector regression. All models were implemented using Python.

The findings revealed the random forest model as the most suitable choice, outperforming the other models considered. The effectiveness of the random forest model varied depending on specific scenarios, particularly the balance between training and testing data set proportions. More importantly, the results identified operational self-sufficiency as the most critical factor influencing the financial performance of MFIs.

This study leveraged machine learning on a well-defined data set to identify the factors predicting the financial performance of MFIs. These insights offer valuable guidance for MFIs aiming to predict their long-term financial sustainability. Investors and donors can also use these findings to make informed decisions when selecting their potential recipients. Furthermore, practitioners and policymakers can use these findings to identify potential financial performance vulnerabilities.

This study stands out by using a global data set to investigate the best model for predicting the financial performance of MFIs, a relatively scarce subject in the existing microfinance literature. Moreover, it uses advanced machine learning techniques to gain a deeper understanding of the factors affecting the financial performance of MFIs.

This article aims to examine the direct and indirect effect among total quality management (TQM), corporate social responsibility (CSR) and financial and non-financial performance.

The empirical data were collected from a survey of 120 Tunisian certified firms using questionnaires. Structural equation path modeling PLS-SEM) was performed to test the research hypotheses.

The results indicate that TQM has no direct effect on financial performance (FP), while they positively impact non-financial performance (NFP) and CSR. The study also shows that CSR positively and significantly influences FP and NFP. In addition, it reveals the positive impact of FP on NFP. Furthermore, the results reveal an indirect effect of TQM on financial and non-financial performance through CSR.

The empirical study bridges the gap in the literature by analyzing the direct and indirect effect between TQM, CSR and performance in a single model. It also highlights the important role of CSR between TQM and financial and non-financial performance in the context of emerging countries.

This paper aims to investigate the impact of retrenchment strategy on firm performance in the context of Pakistani firms while considering the moderating role of chief executive officer (CEO) power. By examining the influence of CEO duality and CEO share ownership on the relationship, this study contributes to strategic management and corporate governance knowledge within the Pakistani business environment.

A quantitative approach was used to analyze the relationship using data from annual financial statements. The sample consisted of 76 companies from the KSE-100 index from the year 2015 to 2020. Random effects regression models were used, along with hierarchical regression to explore the moderating effect of CEO power.

The findings demonstrate that the implementation of a retrenchment strategy positively impacts firm performance in Pakistani firms. The study also reveals that CEO power plays a crucial role in strengthening the relationship between retrenchment strategy and firm performance. Moreover, the study highlights the importance of considering the temporal sequence, size and age of firms when examining the impact of CEO power and retrenchment strategy on firm performance.

The study enhances the understanding of the contingent nature of retrenchment strategies and the influence of CEO power in the Pakistani business context. Practically, the research contributes to strategic management and corporate governance dynamics, facilitating the development of strategies that enhance firm performance and sustainability in Pakistan.

This research provides original insights by specifically focusing on the Pakistani context and analyzing the interplay between retrenchment strategy, CEO power and firm performance. The study adds to the limited literature on the relationship between retrenchment and performance in the Pakistani business environment. Additionally, it highlights the significance of CEO power as a critical factor in determining the success of retrenchment.