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This paper aims to systematically review and synthesize existing research on learning-driven strategic renewal and examines the findings to elucidate the dimensions, antecedents, mechanisms and consequences associated with learning-driven strategic renewal, thereby addressing gaps in the existing literature.

This research covers learning-driven strategic renewal from 1992 to 2022, using hybrid snowball sampling techniques and Boolean searches on the Scopus and Web of Science databases to extract 49 papers.

This review proposes an organizing framework for learning-driven strategic renewal, building upon existing literature. The framework identifies various dimensions of the process, including antecedents, mechanisms and consequences. The antecedents are categorized into individual, organizational and external factors. The mechanisms for learning-driven strategic renewal were explored within the context of Crossan’s established 4I framework, which serves as a lens for emphasizing the balance between exploratory and exploitative learning. Within this framework, intuiting, interpreting, integrating and institutionalizing are the four “Is” that guide the renewal process. These mechanisms require a robust system to enforce the prescribed processes effectively, thereby contributing to long-term firm performance and sustainability.

Despite using search terms similar to those in existing literature on strategic renewal, the scope and depth of this study may be limited. Further research may benefit from bibliometric screening or more refined inclusion criteria.

While there has been extensive research into both organizational learning and strategic renewal, no coherent framework links them. This study fills this gap by building a framework that identifies connections between these two concepts, providing valuable insights that may be used to foster successful strategic renewal efforts. The review offers valuable knowledge and understanding of the subject matter, serving as useful guidance for effectively driving renewal initiatives within organizations.

This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely accepted as a tool to support decision-making processes and for capturing relationships within enterprises.

A systematic literature review (SLR) is conducted using a standard SLR method to provide a comprehensive review of existing literature. The search was conducted on ten platforms identifying 30 publications which were analysed through the use and development of a codebook.

The SLR showed that 90% of the result set consisted of peer-reviewed academic conferences and journal papers. The SLR identified a highly dispersed author set of 83 authors. Amongst these authors, Vinay Kulkarni was an active author who has co-authored up to four publications in this research area. The analysis further revealed that the combined use of SD applications and EE is an emerging research area that still needs to develop in maturity. While all phases of EE have received attention, the current research work is more focused on the design phase. The important gap between model development and implementation is identified.

The study elucidates the existing status of interdisciplinary research combining techniques from the SD and EE disciplines, suggesting future research topics that combine the strengths of these existing disciplines.

The review paper aims to understand the development of workplace ostracism as a field in organizational studies from 2000 to the present. The study provides a comprehensive synthesis of the current state of the domain by exploring its antecedents, consequences, underlying mechanisms and buffering mechanisms.

The present study analyses 134 published peer-reviewed empirical and non-empirical articles retrieved from the Scopus database. A systematic literature review and bibliometric analyses (using VOS viewer) have been used to gain insights into the development and trends within the field. Bibliometric analyses involved science mapping techniques such as co-citation analysis, co-occurrence of keywords and bibliographic coupling. Combining these three techniques, the study aimed to provide a comprehensive overview of the workplace ostracism research domain's historical, current and future landscape.

In the present study, through descriptive analyses, the authors uncovered publishing trends, productive journals, countries and industries that contribute to this research field. The systematic review enabled the showcasing of the current landscape of workplace ostracism. The bibliometric analyses shed light on major authors, influential articles, prominent journals and significant keywords in workplace ostracism.

This study enriches the existing literature by offering a comprehensive research framework for workplace ostracism. It goes beyond that by presenting significant bibliographic insights by applying bibliometric analyses. Furthermore, this study identifies and emphasizes future research directions using the theory, characteristics, construct and methodologies framework, aiming to expand the knowledge base and understanding of this topic.

This study examines current dynamics, consolidates current knowledge, elicits trends, identifies and analyzes primary research clusters, offers future directions, and develops an integrated framework for Product Advantage (PA) research.

Using the SCOPUS database, this study applied bibliometric analysis (208 articles) and conducted content analysis on the 35 curated articles selected using a combination of bibliographic coupling and the most cited articles.

This study presents the field’s publication trends, most relevant authors, articles, journals, and knowledge structures. It identifies six primary research themes and four major clusters using the thematic map and bibliographic coupling. Marketing and PA, New Product Development (NPD) and PA, Product Innovation and PA, and New product speed and PA are the main clusters. Finally, this study offers directions for future research and provides an integrated framework for PA research.

By developing an ADO framework of PA, the study offers key insights into how PA shapes product outcomes and identifies key antecedents of PA. Firms must focus on firm factors such as market and technological orientation; product factors, such as development time and pre-announcement proficiency; external factors, such as competition; and environmental factors, such as competitive intensity and technological turbulence. It enables firms to create products with high PA, shaping product outcomes and contributing to their competitive advantage.

This is the first study to conduct a two-stage sequential hybrid review of quality articles on PA. It offers an Antecedents-Decisions-Consequences (ADO) framework based on significant studies and offers cluster-wise directors for future research.

Intelligent new energy vehicles (INEVs) are becoming the competitive hotspot for the automobile industry. The major purpose of this study is to determine how to increase innovation efficiency through knowledge sharing and technology spill between new energy vehicle (NEV) enterprises and technology enterprises. This will help to improve the core competence of the automobile industry in China. Also, it serves as a guide for the growth of other strategic.

The authors construct a tripartite evolutionary game model to study the cross-border cooperative innovation problem. Firstly, the payment matrix of NEV enterprise, technology enterprise and government is established, and the expected revenue of each participant is determined. Then, the replication dynamic equations and evolutionary stability strategies are analyzed. Finally, the theoretical research is validated through numerical simulation.

Results showed that: (1) An optimal range of revenue distribution coefficient exists in the cross-border cooperation. (2) Factors like research and development (R&D) success rate, subsidies, resource and technology complementarity, and vehicles intelligence positively influence the evolution towards cooperative strategies. (3) Factors like technology spillover risk cost inhibit the evolution towards cooperative strategies. To be specific, when the technology spillover risk cost is greater than 2.5, two enterprises are inclined to choose independent R&D, and the government chooses to provide subsidy.

The research perspective and theoretical analysis are helpful to further explore the cross-border cooperation of the intelligent automobile industry. The findings suggest that the government can optimize the subsidy policy according to the R&D capability and resource allocation of automobile industry. Moreover, measures are needed to reduce the risk of technology spillovers to encourage enterprise to collaborate and innovate. The results can provide reference for enterprises’ strategic choice and government’s policy making.

The INEV industry has become an important development direction of the global automobile industry. However, there is limited research on cross-border cooperation of INEV industry. Hence, authors construct a tripartite evolutionary game model involving NEV enterprise, technology enterprise and the government, and explore the relationship of cooperation and competition among players in the INEV industry, which provides a new perspective for the development of the INEV industry.

In the present study, we examined how effectively online travel agencies (OTAs) handle negative e-word-of-mouth on social media platforms like Facebook, Twitter, and Instagram. We collected data from 497 participants using survey method. To test the hypotheses formulated from the existing literature, structural equation modeling was adopted in this study. The results from structural equation modeling indicate effective handling of the negative e-word of mouth (e-WOM) on social media websites significantly affects customer satisfaction and repurchase intention. The current research work provides insight into social media recovery efforts and service fairness when handling negative e-WOM. The study recommends that customers can distinguish the differences between general efforts and adaptive complaint-handling efforts, and dissimilarities may influence satisfaction, repurchase intentions, etc. Although empathy, apology, responsiveness, and paraphrasing are considered pioneer strategies in complaint handling, customers' negative e-WOM, and firms' recovery management, but the current study is among a few to categorize OTAs' handling of negative e-WOM and complaint handling efforts in the social media environment.

This study aims to develop an empathetic and user-centric customer support service design model. Though service design has been a critical research focus for several decades, few studies focus on customer support services. As customer support gains importance as a source of competitive advantage in the present era, this paper aims to contribute to industry and academia by exploring the service design model.

The study adopted a theories-in-use approach to elucidate mental models based on the industry’s best practices. In-depth interviews with 62 professionals led to critical insights into customer service design development, supported by service-dominant logic and theory of mind principles.

The ensuing insights led to a model that connects the antecedents and outcomes of empathetic and user-centric customer service design. The precursors include people, processes and technology, while the results are user experience, service trust and service advocacy. The model also emphasises the significance of the user’s journey and the user service review in the overall service design.

The model developed through this study addresses the critical gap concerning the lack of service design research in customer support services. The key insights from this study contribute to the ongoing research endeavours towards transitioning customer support services from an operational unit to a strategic value-creating function. Future scholars may investigate the applicability of the empathetic user service design across cultures and industries. The new model must be customised using real-time data and analytics across user journey stages.

The empathetic and user-centric design can elevate the customer service function as a significant contributor to the overall customer experience, loyalty and positive word of mouth. Practitioners can adopt the new model to provide superior customer service experiences. This original research was developed through crucial insights from interviews with senior industry professionals.

This research is the original work developed through the key insights from the interview with senior industry professionals.

The purpose of this study is to investigate when and why supervisor negative feedback is associated with employees' job performance via two different pathways (i.e. emotion-focused coping and problem-focused coping) and to introduce proactive personality as a moderator.

Time-lagged data were collected using a field survey research design. Participants included 389 dyads of employees and their direct supervisors from five companies in China.

Supervisor negative feedback can lead to employees' emotion-focused coping, which in turn impairs their job performance. Meanwhile, supervisor negative feedback can trigger employees’ problem-focused coping, which subsequently promotes their job performance. Furthermore, proactive personality moderates the indirect effect of supervisor negative feedback on employee performance through emotion-focused coping.

This study explored the double-edged effects of supervisor negative feedback on employee job performance from a coping strategy perspective and investigated how proactive personality influences the choice of coping strategies.

In recent times, the field of corporate intelligence has gained substantial prominence, employing advanced data analysis techniques to yield pivotal insights for instantaneous strategic and tactical decision-making. Expanding beyond rudimentary post observation and analysis, social media analytics unfolds a comprehensive exploration of diverse data streams encompassing social media platforms and blogs, thereby facilitating an all-encompassing understanding of the dynamic social customer landscape. During an extensive evaluation of social media presence, various indicators such as popularity, impressions, user engagement, content flow, and brand references undergo meticulous scrutiny. Invaluable intelligence lies within user-generated data stemming from social media platforms, encompassing valuable customer perspectives, feedback, and recommendations that have the potential to revolutionize numerous operational facets, including supply chain management. Despite its intrinsic worth, the actual business value of social media data is frequently overshadowed due to the pervasive abundance of content saturating the digital realm. In response to this concern, the present study introduces a cutting-edge system known as the Enterprise Just-in-time Decision Support System (EJDSS).

Leveraging deep learning techniques and advanced analytics of social media data, the EJDSS aims to propel business operations forward. Specifically tailored to the domain of marketing, the framework delineates a practical methodology for extracting invaluable insights from the vast expanse of social data. This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.

To substantiate the efficacy of the EJDSS, a detailed case study centered around reverse logistics resource recycling is presented, accompanied by experimental findings that underscore the system’s exceptional performance. The study showcases remarkable precision, robustness, F1 score, and variance statistics, attaining impressive figures of 83.62%, 78.44%, 83.67%, and 3.79%, respectively.

This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.

Drawing on conservation of resources theory, this study aims to examine how employees’ experiences of excessive workloads may direct them away from efforts to share knowledge with other organizational members, as well as the circumstances in which this process is more or less likely. To untangle the process, the authors predict a mediating role of job dissatisfaction and moderating roles of two complementary resources that help employees cope with failure: resilience as a personal resource and organizational forgiveness as an organizational resource.

Survey data were gathered from employees of an organization that operates in the construction retail sector. The Process macro provides an empirical test of the moderated mediation dynamic that underpins the proposed conceptual framework.

The statistical findings affirm that an important channel through which employees’ perceptions that their work demands are unreasonable escalate into a diminished propensity to share knowledge is their lack of enthusiasm about their jobs. Their ability to recover from challenging work situations and their beliefs that the organization does not hold grudges against people who commit mistakes both mitigate this harmful effect.

For organizational practitioners, this research shows that when employees feel frustrated about extreme work pressures, the resource-draining situation may escalate into diminished knowledge sharing, which might inadvertently undermine their ability to receive valuable feedback for dealing with the challenges. From a positive perspective, individual resilience and organizational forgiveness represent resources that can protect employees against this negative spiral.

This study explicates an unexplored harmful effect of strenuous workloads on knowledge sharing, which is explained by employees’ beliefs that their organization fails to provide satisfactory job experiences. This effect also is mitigated to the extent that employees can draw from valuable personal and organizational resources.