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This paper aims to investigate the performance of OECD countries' long-term productivity during the period of 1975–2018.

This study employed different approaches to evaluate how efficiency scores vary with changes in inputs and outputs: Data Envelopment Analysis (CRS, VRS and FDH), TOPSIS and TOPSIS of these scores.

The findings suggest that, during the period of this study, countries with higher freedom of religion and with Presidential democracy regimes are positively associated with higher productivity.

To the best of the authors’ knowledge, this is the first study that uses efficiency models to assess the productivity levels of OECD countries based on several contextual variables that can potentially affect it.

Multi-criteria decision-making (MCDM) techniques are decision support systems that provide systematic approaches to solve hospitality and tourism (H&T) problems while minimizing the risk of failure. However, less is known about the application of MCDM techniques in H&T research. This study aims to systematically assess the use of MCDM techniques in H&T research to classify its current application and determine its application potential for H&T research.

This study used bibliometric analysis to examine all published MCDM studies focused on H&T industries, since 1997. In addition, topic modelling was used to discover key concepts. Finally, top cited studies in terms of total citations per year and total citations were qualitatively reviewed for more insights.

The findings revealed an ongoing interest in applying MCDM techniques in H&T research. Specifically, the extension of fuzzy theory in MCDM techniques is burgeoning among H&T researchers. However, a certain number of MCDM techniques seem to be ignored in this field with a repetitive application of MCDM techniques in particular areas.

The data for the current research was solely retrieved from Scopus and other databases were not included. Therefore, future research is called for to re-examine the study by considering data from various databases.

This study contributes to extant H&T literature by identifying the most prolific and influential countries, journals, publications and trends by applying MCDM techniques in H&T research, and elucidating the implications and characteristics of MCDM techniques in H&T research.

Agricultural sector not only meets the nutritional requirements of all living creatures but also generates the primary source of the raw material provided by various branches of industry to fulfill their functions. It is of great importance to increase studies on oilseeds which have an important role in Turkey's agricultural products. They are grown in almost all of the country, which are vital for the nutrition and many sectors. The main purpose of the study is to offer an integrated approach to determine potential warehouse locations for oilseeds.

This is the first study that integrates Delphi, analytical hierarchical process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), P-Median and Panel data analysis in a real case. This integrated approach consists of the following steps, respectively: (1) The criteria were determined by the Delphi method. (2) The weights of the criteria were calculated by AHP and the provinces with the highest oilseed warehouse potential in seven regions of Turkey were specified by TOPSIS. (3) Oilseed warehouse numbers and locations were obtained by P-Median. (4) In order to answer whether the distribution network is profitable in the future with the determined center locations, a forecast model based on panel data analysis was created. (5) Regional representatives were determined for 2030, and the distribution network was analyzed again. (6) The costs that arose in 2018 and 2030 were computed and compared by cost analysis. (7) The effect of the change in criteria weights on the alternative results was tested by scenario analysis.

The findings indicated that oilseed crop production potential and oilseed crop production area turned out to be the most important criteria. Furthermore, the results showed that this model is robust and suitable for warehouse location selection studies.

The study can serve as a guide for local and central policy makers with both the criteria it uses and the model it develops.

The main contribution of this study is that the integrated approach has been used for the first time in location selection in a real case.

Dynamic governance practices are key in the administration of 21st-century airlines. Knowledge transfer via the fourth industrial revolution (4IR) is germane in governance practices. Studies have proven that the 4IR technologies could enhance airline governance and improve safety measures and productivity. The 4IR role in improving airline governance is yet to receive in-depth studies in South Africa. Thus, this study aims to investigate the governance challenges facing South African airlines in the era of 4IR.

This research used a qualitative research method. The main data were collected via 56 face-to-face semi-structured interviews with key stakeholders. The research achieved saturation. A thematic technique was used to analyse the collected data.

Findings reveal 12 challenges and are grouped into six governance barriers facing South African airlines in the era of 4IR. Also, findings suggest measures to mitigate governance barriers and promote 4IR technologies usage in the airline sector.

The study assesses critical governance challenges facing South African airlines in the era of 4IR. Understanding the importance of vital governance challenges can assist critical stakeholders in promoting innovative policies and regulations tailored towards digitalised aerospace. Thus, the study contributes strategies to improve digital innovation and reduce airline risks in South Africa. Also, it contributes to the paucity of academic literature on developing countries’ airline governance in the 4IR era and the South African aviation sector.

This paper explores the nonlinear interactions of research and development (R&D) and advertising and their synergistic effect on firm performance using Tobin's Q. This study also aims to investigate differential synergy patterns under varying levels of exports with a precision impact on performance.

Unlike a conventional statistical approach, this study uniquely presents a neural network approach to explore the dynamic interplay of strategic factors. A multilayer perceptron neural network (MPNN) is designed to capture complex interaction patterns through a predictive analytic process.

This study finds that the impact of R&D and advertising is positive, with a greater effect on high-export firms. Moreover, the experiment results show that the synergy of R&D and advertising goes beyond the formatted positive/negative frame and actually has a reinforcing effect.

This study not only conveys the significant nexus of R&D and advertising for firm performance but also provides industry managers' practical means to assess the joint effect of R&D and advertising on firm performance. The proposed analytic mechanism in particular provides pragmatic decision support to managers in harmonizing their R&D and advertising efforts for a foreseeable impact.

This paper presents an innovative analytic process using the MPNN to explore the synergy between R&D and advertising. In addition to offering new perspectives on R&D and advertising, this study presents pragmatic implications for managing those strategic resources to meet performance targets.

This study aims to present the cost and revenue efficiency evaluation models in data envelopment analysis in the presence of fuzzy inputs, outputs and their prices that the prices are also fuzzy. This study applies the proposed approach in the energy sector of the oil industry.

This study proposes a value-based technology according to fuzzy input-cost and revenue-output data, and based on this technology, the authors propose an approach to calculate fuzzy cost and revenue efficiency based on a directional distance function approach. These papers incorporated a decision-maker’s (DM) a priori knowledge into the fuzzy cost (revenue) efficiency analysis.

This study shows that the proposed approach obtains the components of fuzzy numbers corresponding to fuzzy cost efficiency scores in the interval [0, 1] corresponding to each of the decision-making units (DMUs). The models presented in this paper satisfies the most important properties: translation invariance, translation invariance, handle with negative data. The proposed approach obtains the fuzzy efficient targets corresponding to each DMU.

In the proposed approach, by selecting the appropriate direction vector in the model, we can incorporate preference information of the DM in the process of evaluating fuzzy cost or revenue efficiency and this shows the efficiency of the method and the advantages of the proposed model in a fully fuzzy environment.

Embeddedness has gained prominence in entrepreneurship studies. However, the notion that the embeddedness metaphor relates to “market” structures prevails in studies in the area. Entrepreneurship scholars still know little about whether entrepreneurs are eventually embedded in other structures whose relationships go beyond the restricted dimension of the interested actor’s assumption. This study aims to propose investigating the social structures in which a specific type of entrepreneurship, the religious one, is embedded.

The research was qualitative, using interviews as an evidence collection instrument. A total of 17 entrepreneur-pastors responsible for business churches in Brazil and eight parishioners took part in the study.

Religious entrepreneurs are embedded in market structures, corroborating a perspective that associates embeddedness with the utilitarian notion. At the same time, entrepreneurs are embedded in two other social structures: reciprocity and redistribution.

This article emphasizes the relevance of going beyond the predominant perspective associated with the utilitarian and rationalized understanding of embeddedness in relationship networks.

This study makes essential contributions. Initially, it attests to the utilitarian perspective of Granovetter’s embeddedness while suggesting incorporating two other dimensions into the metaphor. By highlighting this, this article stresses the need to reinterpret the metaphor of embeddedness and how entrepreneurship scholars use it. Further, by emphasizing the need to consider embeddedness in networks beyond its still utilitarian perspective, this paper highlights unexplored opportunities for entrepreneurship scholars.

This paper aims to present two-stage network models in the presence of stochastic ratio data.

Black-box, free-link and fix-link techniques are used to apply the internal relations of the two-stage network. A deterministic linear programming model is derived from a stochastic two-stage network data envelopment analysis (DEA) model by assuming that some basic stochastic elements are related to the inputs, outputs and intermediate products. The linkages between the overall process and the two subprocesses are proposed. The authors obtain the relation between the efficiency scores obtained from the stochastic two stage network DEA-ratio considering three different strategies involving black box, free-link and fix-link. The authors applied their proposed approach to 11 airlines in Iran.

In most of the scenarios, when alpha in particular takes any value between 0.1 and 0.4, three models from Charnes, Cooper, and Rhodes (1978), free-link and fix-link generate similar efficiency scores for the decision-making units (DMUs), While a relatively higher degree of variations in efficiency scores among the DMUs is generated when the alpha takes the value of 0.5. Comparing the results when the alpha takes the value of 0.1–0.4, the DMUs have the same ranking in terms of their efficiency scores.

The authors innovatively propose a deterministic linear programming model, and to the best of the authors’ knowledge, for the first time, the internal relationships of a two-stage network are analyzed by different techniques. The comparison of the results would be able to provide insights from both the policy perspective as well as the methodological perspective.

The authors study the effect of increasing environmental awareness on shareholders' activism. Specificallly, this study aims to examine whether growing environmental awareness is reflected in more aggressive environmental shareholder proposals.

This study uses the 2010 Deepwater Horizon oil spill disaster as an exogenous event that increased shareholders' environmental awareness. This study analyzes the spill’s effect on the tone of proposals about environmental issues and nonenvironmental topics.

After the disaster, the tone of environmental proposals (i.e. the treatment group) is significantly more negative. In contrast, the tone of nonenvironmental proposals (i.e. the control group) is unaffected. This study interprets this finding as direct evidence that the oil spill led to increased shareholder environmental activism through proposals that targeted the environmental risks surrounding the business more aggressively. By contrast, this study finds no effect of the oil spill on the tone of managers' responses to the proposals, consistent with managers refraining from emphasizing environmental threats.

Anecdotal evidence and recent studies suggest a link between environmental disasters and shareholder pressure for corporate change. However, no prior research has investigated the channel through which shareholders could have exerted such pressure or has looked for direct evidence of it in the negotiations between shareholders and managers. By finding such evidence in shareholder proposals, this study fills in this gap.

The COVID-19 epidemic has brought attention to the variables that influence the mental health of health workers who are entrusted with nursing individuals. Despite the fact that many articles have examined the effects of social media usage on mental health, there is a lack of research synthesizing learning from this body of research. The purpose of this study is to use text mining and citation-based bibliometric analysis to conduct a detailed review of extant literature on health workers’ mental health and social networking habits.

This study conducts a full-text analysis of 36 articles selected on health workers' mental health and social media using text-mining techniques in R programming and a bibliometric citation analysis of 183 papers from the Scopus database in VOS viewer software. But the limitations of the methods used in this study are that the bibliometric analysis was limited to the Scopus database because the VOS viewer program did not support any other database and the text-mining approach caused the natural processing redundancy.

The bibliometric analysis reveals the thematic networks that exist in the literature of health workers’ mental health and social networking. The findings from text mining identified ten topic models, which helped to find the related papers classified in ten different groups and are provided alongside a summary of the published research and a list of the primary authors with posterior probability through Latent Dirichlet Allocation.

To the best of the authors’ knowledge, this is the first hybrid review, combining text mining and bibliometric review, on health workers’ mental health where social networking plays a moderating role. This paper critically provides an overview of the impact of social networking on health workers' mental health, presents the most important and frequent topics, introduces the scientific visualization of articles published in the Scopus database and suggests further research avenues. These findings are important for academics, health practitioners and medical specialists interested in learning how to better support the mental health of health workers using social media.