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This study aims to explore the drivers (i.e. service innovation, service exchange, customer wellbeing and employee wellbeing) and organizational culture in the service ecosystem in the hospitality sector.

This study adopted a quantitative approach by collecting data from employees and customers of the top 10 hotels (identified from three major websites, i.e. Goibibo, Trivago and MakeMyTrip) functional in Jammu city, North India. Exploratory factor analysis, confirmatory factor analysis and partial least square analysis are used to analyse the data.

The study findings reveal that among the four drivers (i.e., service innovation, service exchange, employee wellbeing and customer wellbeing) customer wellbeing shows a strong impact and significant impact on the service ecosystem. Following this, the study also exhibits that organizational culture significantly moderates the relationship between service innovation and the service ecosystem. However, it does not show any moderating influence among the other drivers of the service ecosystem.

This study is conducted only in the top 10 hotels (three and four stars) of Jammu city, North India, which might not represent all Indian hotels.

The study contributes by establishing the role of four service ecosystem drivers, namely service innovation, service exchange, employee wellbeing and customer wellbeing. Following this, the study empirically tested and validated the service ecosystem framework in the context of north Indian hotels. The study also establishes the significant role of organizational culture, particularly group culture and hierarchy culture, in strengthening the service ecosystem.

The development of online brand communities employed by marketers to maintain consumer relationships and brand building is increasing. This study aims to explore how value co-creation practices can cultivate consumers' brand loyalty.

Using partial least squares modeling, the hypotheses testing involves the utilization of and data collection from 599 Chinese consumers who actively engage in brand communities in China.

Value co-creation practices in brand communities cultivate consumers' affective commitment and psychological brand ownership, which in turn can further contribute to consumers' brand loyalty.

By offering a more comprehensive insight into how affective commitment and psychological brand ownership act as intermediaries between value co-creation practices and consumers' brand loyalty, this research enhances the existing knowledge on value co-creation and brand management.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

This study aims to investigate the relationship between corporate sustainable development goals (SDGs) disclosure and analyst forecast quality.

The study focuses on a sample of 95 Italian-listed companies preparing the mandatory non-financial declaration (NFD) according to the Global Reporting Initiative (GRI) standards over a five-year period (2017–2021), corresponding to an unbalanced sample of 438 observations. Analyst forecast quality was proxied by earnings forecast accuracy (FA) and earnings forecast dispersion (FD), built on data retrieved from the Refinitiv database. A manual content analysis was performed on NFDs to derive an SDG disclosure score (SDGD) for each sampled company.

This study provides empirical evidence suggesting that voluntary SDG disclosure matters to the capital market in that it helps enhance the information environment of companies, evidenced by improved analyst forecast quality. In particular, this study highlighted that SDG disclosure positively influences analyst FA while negatively affecting analyst FD.

This study focuses on the Italian context, which has idiosyncratic characteristics regarding the structure of the financial market, the composition of corporate ownership and experience in non-financial reporting practices.

This study indicates to corporate managers that following GRI standards may represent the right way to better integrate SDG disclosure in corporate non-financial reports and increase the relevance of such information for investors and other capital market participants.

To the best of the authors’ knowledge, this is the first study that empirically examines the association between SDG disclosure and analyst forecast quality.

The link between interlocking directors and mergers and acquisitions (M&A) efficiency has been analyzed in an information asymmetry environment. Despite an abundance of evidence highlighting that interlocking directors do contribute to M&A efficiency in an acquirer-target binary relationship, the target is embedded in a complex network of supplier-customer relationships, which implies that the acquirer needs to consider the value of suppliers, distributors and retailers in the target’s supply chain in improving M&A efficiency. Through the lenses of acquirer-target multivariate relationships, this paper aims to examine how directors with supply chain experience (DSCs) act as heterogeneous network pipes to affect M&A efficiency.

Using a sample of 311 A-share listed firms on the Shanghai and Shenzhen stock exchanges in China during 2011–2020, this paper investigates the relationship between DSCs and M&A efficiency by using ordinary least squares (OLS) regression.

Through empirical research, we verify a negative relationship between DSCs and M&A duration and an inverted U-shaped relationship between both DSCs and M&A performance, revealing the complexity of the relationship between experience and efficiency. Furthermore, drawing on upper echelon theory, the information value of DSCs will be greatly reduced when executives have overconfident psychological characteristics, which are mainly shown to negatively moderate the relationship between DSCs and M&A performance. We also conduct multiple robustness tests and supplemental analyses to illustrate the robustness and boundaries of our findings. Finally, DSCs are likely more important in environments among growth and mature firms as well as high-growth industries.

We break through the assumption that interlocking directors contribute to M&A efficiency in an acquirer-target binary relationship and examine the impact of DSCs on M&A efficiency based on micro-empirical evidence from the value of target-related upstream or downstream industries, which extends the connotation of interlocking directors and enriches the study related to factors influencing M&A efficiency.

Engaging suppliers in joint innovation can be an effective means for buyer firms to overcome internal resource/capability limitations. The purpose of this research is to investigate the impacts of cultural and trust congruences between the supplier and buyer firms on joint innovation. In addition, we examine the relationship commitment as an antecedent of cultural and trust congruences.

The study constructs a theoretical model based on social exchange theory (SET) and examines it using data from Chinese manufacturing firms.

The results suggest that cultural and trust congruences between suppliers and buyers positively influence joint processes and product innovations. Furthermore, we find that while normative relationship commitments of supplier firms promote cultural and trust congruences with buyers, instrumental relationship commitments only positively affect trust congruence.

This study enhances our understanding of social exchanges by adopting a dyadic view to examine the interconnectedness between relationship commitment, cultural and trust congruences, and joint innovation. These findings also offer practical managerial implications for managing collaborative innovation projects.

In order to improve the computation efficiency of the four-point rainflow algorithm, a new fast four-point rainflow cycle counting algorithm (FFRA) using a novel loop iteration mode is proposed.

In this new algorithm, the loop iteration mode is simplified by reducing the number of iterations, tests and deletions. The high efficiency of the new algorithm makes it a preferable candidate in fatigue life online estimation of structural health monitoring systems.

The extensive simulation results show that the extracted cycles by the new FFRA are the same as those by the four-point rainflow cycle counting algorithm (FRA) and the three-point rainflow cycle counting algorithm (TRA). Especially, the simulation results indicate that the computation efficiency of the FFRA has improved an average of 12.4 times compared to the FRA and an average of 8.9 times compared to the TRA. Moreover, the equivalence of cycle extraction results between the FFRA and the FRA is proved mathematically by utilizing some fundamental properties of the rainflow algorithm. Theoretical proof of the efficiency improvement of the FFRA in comparison to the FRA is also given.

This merit makes the FFRA preferable in online monitoring systems of structures where fatigue life estimation needs to be accomplished online based on massive measured data. It is noticeable that the high efficiency of the FFRA attributed to the simple loop iteration, which provides beneficial guidance to improve the efficiency of existing algorithms.

The study aims to delve into the “phygital customer journey” (PCJ), which merges physical and digital interactions in customer experiences, using a practice-based lens to reveal the underlying dynamics of these blended encounters.

Feedback from 60 individuals established the groundwork for a qualitative analysis. They chronicled customer journeys through diaries and used UXPressia software for journey mapping. This strategy enabled a detailed exploration of the PCJ, focusing on customers’ lived experiences and perceptions.

The study presents an integrative framework for the PCJ, identifying four key elements: hybrid artefacts (the melding of digital and physical tools/interfaces), blended contexts (the seamless integration of digital and physical spaces), circular actions (the non-linear paths of customer engagement) and intertwined emotions (the complex emotional responses to phygital experiences). These elements underscore the intricate and interconnected nature of the PCJ.

This study advances the field by applying a practice-based approach to unravel the complexities of the PCJ, illuminating the nuanced interplay between digital and physical realms. This innovative lens foregrounds the significance of practices in consumer experiences, thereby contributing to a deeper academic and practical understanding of phygital integration.

This study aims to examine how different uses of performance measurement systems (PMS) enable or hinder organizational ambidexterity (OA), intended as the simultaneous pursuit of exploitation and exploration.

Following a qualitative research design, we gathered data through semi-structured interviews, observations and reviews of documents at four departments of an automotive firm.

We contribute to operations management research and practice by demonstrating how PMS, which are typically associated with exploitation, can also foster exploration and enable organizations to become ambidextrous. Specifically, we show how PMS can be structured and used in more agile ways and, in relation to innovation, we identify which PM practices should be introduced and with what effects and those that should be avoided. We also contribute to organization theory by highlighting how a single management tool can promote the achievement of both exploration and exploitation.

In investigating PMS uses and their effects, we identify several positive practices. For example, we show how managers can use PMS more effectively and how targets could be deployed to stimulate creativity and innovation. We also emphasize the need for managers to opt more often for team incentives rather than individual ones to encourage the collaboration needed for OA.

We provide in-depth insight into how PM tools affect an organization’s ability to pursue exploitation and exploration, thus contributing to research in operations, innovation and organization theory.

This study aims to conceptualize, rethink and systematize methods used for measurement and evaluation (M&E) corporate communication.

The reflection is based on 462 key English-language books and papers devoted to M&E in the fields of corporate communication and public relations from the 1970th to 2023. Keywords in the titles and abstracts found the necessary materials. A critical analysis of the central concepts, models and methods described in the literature was conducted. As a result, a new model that unifies and structures the M&E toolkit is proposed for discussion.

Despite the significant contribution to developing a wide range of M&E models, they are still not perfect and universal. In addition, this system of approaches is continuously self-evolving and changing under the influence of digital innovations, so it requires steady rethinking and updating. On the other hand, most previous studies focused on communication management processes, losing focus on communication aspects. This led to the need for an alternative view based on proven theories to fill this gap. The proposed model combines quantitative and qualitative M&E methods for the five main components of corporate communication (communicator, audience, content, channels and result), covering a wide range of tools, from statistical and sociological research to big data analysis and neuro research.

This work contributes to developing the M&E theory of corporate communication, systematizing existing methods and opening new research perspectives. From a practical point of view, companies can use the presented approach for a more accurate and objective internal evaluation of the main components of corporate communication.