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As an increasingly important variable in the career field, career sustainability has received particular attention, yet few empirical studies have been conducted to examine its antecedents. The authors propose a moderated mediation model based on the goal-setting theory and the wise proactivity perspective for exploring when and how self-goal setting can influence career sustainability.

The authors use a time-lagged design and collect three waves of data from 1,260 teachers in basic education schools in China. The authors test the proposed hypotheses with SPSS 26.0 and Mplus 8.3.

The results show that self-goal setting positively relates to career sustainability and that career crafting plays a mediating role in this relationship. This relationship is strengthened when perceived organizational goal clarity is high.

The authors extend the application scenarios of the goal-setting theory to the field of career research and find out that self-goal setting is also a self-initiated and wise antecedent of career sustainability. From a wise proactivity perspective, the authors examine the mediating mechanism of career crafting to make positive career outcomes. Furthermore, the authors consider the impact of perceived organizational goal clarity as a boundary condition and broaden the understanding of “when to wise proactivity” from the goal-setting theory.

Due to the popularity of mobile devices and the development of artificial intelligence (AI), AI-powered mobile fitness applications (MFAs) have entered people's daily lives. However, the extant literature lacks empirical investigations that explore users' continuance usage intentions regarding AI-powered MFAs. To fill this research gap, this paper employs goal-setting theory to establish a research model for exploring how AI-enabled features (i.e. intelligence and anthropomorphism) affect users' perceptions of goal difficulties and goal specificities, which in turn affect their MFA continuance usage intentions.

This paper uses a survey method to analyze the research model, and a total of 223 responses are collected. The partial least squares (PLS) technique is utilized for data analysis.

The results show that intelligence and anthropomorphism affect the continuance usage intention of MFA users through their goal difficulty and specificity. Both intelligence and anthropomorphism positively influence goal specificity, whereas they negatively affect goal difficulty. In addition, goal specificity increases users' MFA continuance usage intention, whereas goal difficulty decreases users' continuance usage intention. The findings of this study provide theoretical contributions for AI technology adoption research and offer practical strategies for firms to retain MFA users.

Based on goal-setting theory, this study reveals that as two primary AI features of contemporary mobile fitness apps, intelligence and anthropomorphism, can increase comprehension of users' perceptions regarding goal difficulty and specificity in the context of users' continuance usage intentions toward AI-powered MFAs.

In recent years, rough set theory has evolved as one of the most promising classification techniques. One of the cardinal uses of rough set theory is its application for rule generation. The purpose of this paper is to propose a real-time fabric inspection technique. This work deals with the multi-class classification of fabric defects using rough set theory.

This technique focuses on the classification of fabric defects using the effective decision rules envisaged by rough set theory. In the proposed work, the six features of 50 images have been used for multiclass classification of fabric defects.

In this work, 40 images were used for generation of decision rules and 10 unseen images were used for validation out of which nine images are accurately predicted by the proposed technique.

The proposed method accurately identified 9 out of 10 testing defects. The obtained decision rules provide an insight about the classification method which ensures that the prediction accuracy can be improved further by framing more robust decision rules with the help of a large training data set. Thus, with the support of modern computational systems this method is potent in getting recognition from the textile industry as a real-time classification technique.

This chapter demonstrates a parallel between the presidential campaigns of Jair Bolsonaro (Brazil, 2018) and Donald Trump (United States, 2016) regarding their use of social media. Specifically, tweets from the former candidates on the social network sites were analyzed during a one-month timeframe before their respective presidential elections. Tweets were selected for analysis based on the fact that Twitter was the main platform used by both former presidential candidates. The analysis of the data reveals considerable similarities between the communication strategies of the two candidates. This research enlists McCombs and Shaw (1972) agenda setting theory based on their study of media during North American presidential campaigns in 1968 and Lippmann’s (2008) concept of public opinion. The methodology employed is based on Bardin (2011).

This study aims to comprehend luxury brands' corporate social responsibility (CSR) strategies. In addition to facing a demand for new CSR strategies (consumer-centric CSR), changes in CSR discourse among luxury brands are observed. This study examines how CSR-related and luxury-related agendas relate in the news media, especially concerning the difference between traditional and new luxury brands.

A total of 117,171 fashion-related news articles were collected from January 2016 to December 2020. The word2vec method was used to determine the relationship between CSR and luxury agendas.

The results indicate that company-centric CSR is more prominent with traditional luxury brands, while consumer-centric CSR is more relevant for new luxury brands. In addition, specific CSR attributes and luxury-related attributes are associated with media discourse, which means that CSR and luxury are compatible.

Studies on CSR in the luxury industry are not extensive in the literature. This study addresses this gap through a unique framework that combines agenda-setting theory and existing CSR literature and applies them to the luxury industry. Specifically, this study captures the development of each construct (company-centric CSR to consumer-centric CSR and traditional luxury to new luxury) and identifies the specific relationships between them. This result provides a novel view of the luxury industry indicating that it has evolved to encompass CSR-related values. The empirical results also offer practical implications for luxury marketing.

Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems.

To achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives.

The feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach.

The proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.

A new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.

Prior studies on the impact of incentives on physicians’ online participation mainly focused on different incentives while ignoring the difficulty of setting monetary incentives efficiently. Based on goal-setting theory, the current research examines the relationship between incentives with goals of varying difficulty and professional health knowledge sharing (PHKS) in online health knowledge-sharing platforms (OHKSPs).

Four field experiments with different monetary incentives were conducted by one of China’s largest OHKSPs, with whom the researchers cooperated in data collection. Monthly panel data on 10,584 physicians were collected from September 2018 to December 2019. There were 9,376 physicians in the treatment group and 1,208 in the control group. The authors used a difference-in-difference (DID) model to explore the research question based on the same control group and the Chow test with seemingly unrelated estimation (sureg) to compare regression coefficients between four groups. Several robustness checks were performed to validate the main results, including a relative time model, multiple falsification tests and a DID estimation using the propensity score matching method.

The results show that the monetary incentive significantly positively affected the volume of physicians’ PHKS directly with negative spillover to the duration of physicians’ PHKS. Moreover, the positive effect of incentives with higher difficulty on the volume of physicians’ PHKS was significantly smaller than that of incentives with low difficulty. Finally, professional title had a positive moderating effect on the volume of goal difficulty setting and did not significantly moderate the effect on the duration of physicians’ PHKS.

Some limitations of this study are: firstly, because the field experiments were enterprise benefit oriented, the treatment and control groups were not balanced. Secondly, the experiments for different incentive measures were relatively similar, making it challenging to validate a causal effect. Finally, more consideration should be given to the strategy for setting hierarchical incentives in future research.

The research indicates that monetary incentives have a bilateral effect on PHKS, i.e. a positive direct effect on the volume of physicians’ contributions and a negative spillover effect on the duration of physicians’ PHKS. The professional titles of physicians also moderate such bilateral switches of PHKS. Furthermore, when a physician’s energy is limited, the goal difficulty setting of the incentive mechanism tends to be low. The more difficult the incentives are, the more inefficient the effects on physicians’ PHKS will be.

This study aims to construct a scale and identify the factors that might affect the implementation of gamification and Bloom's Digital Taxonomy-based assessment of students' learning, guided by the Goal-Setting Theory.

This study used a sequential exploratory mixed-methods design where data were collected qualitatively via interviews (n = 18) and field notes. Quantitative analysis was then applied via questionnaires (n = 96).

Four major themes emerged following thematic analysis of the observation notes and interview data: learning engagements; understandable learning goals; friendly competitions; and interactive learning feedback. A scale consisting of 32 items was developed based on the qualitative data. The quantitative data were then collected to evaluate the scale's factor structure using maximum likelihood exploratory factor analysis with Promax factor rotation. The final version of the scale had 29 items. The authors verified the alpha coefficients for each element and the entire hierarchy, ranging from 0.94 to 0.98 for the factors. The total scale was determined to be 0.96, and the Item Content Validity Index was considered valid.

The scale developed in this study is expected to inform future research and guide educators who wish to incorporate contemporary digital pedagogies in a different context. This study could also be beneficial to researchers who aspire to perform research on Goal-Setting Theory in the educational context.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

Sustainability continues to be put forth as a strategic priority. However, sustainability efforts are often deemphasized for short-term profitability. This study explores the nuances in managerial decision-making related to adopting sustainability initiatives within food supply chains in an emerging economy. We identify a complex interaction between sustainability efforts and risk mitigation. We derive a model to explain conflicting company goals, managerial decisions and system design.

We followed an exploratory research design with an inductive approach. We analyzed data from semi-structured interviews with 29 companies representing different tiers in Turkish food supply chains. We refined and validated the interview findings through a focus group with nine senior managers. We conducted open, focused and theoretical coding in an iterative and reflective manner to analyze the data and derive our results.

From the data, three themes emerged, indicating that managers are pursuing different, often conflicting, goals concerning value creation, risk management and sustainability performance. Managers identified and commented on new risks brought on by sustainability initiatives. These sustainability-induced risks were seen as a threat to operational performance, a driver of increased costs and a negative impact on product quality and delivery performance. Trade-offs across operating, sustainability and risk management systems create transformational tension that confounds the sustainability adoption decision-making process.

The data from the study was contrasted with a theoretical framework derived from systems theory, goal-setting theory of motivation and the theory of planned behavior. We identified four distinct decision paths that managers pursue. Increased awareness of transformational tension and how it influences managerial decision-making can enhance strategic sustainability system design and initiative success.