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This study aims to investigate the role of multidimensional social capital and consumer subjective well-being in online brand communities (OBCs). The aim was to provide practical guidance to global brand marketers for cultivating and strengthening OBC operations, optimizing consumer-brand-community relationships and creating value in the digital age.

A total of 576 valid questionnaires were collected through an online survey, and the model was tested using partial least squares structural equation modeling.

In OBCs, the cognitive dimension of social capital (i.e. shared language and shared vision) strongly affects the relational dimension of social capital (i.e. social trust and reciprocity). Both these dimensions also positively influence consumer community subjective well-being, which, in turn, enhances consumer brand subjective well-being. Thus, community subjective well-being has a mediating role in the aforementioned relationship, and brand community is an antecedent to brand subjective well-being.

Future studies should investigate other dimensions of social capital and well-being, as well as moderator variables, social environments and types of culture.

This study constructed a conceptual framework that focused on the effect of multidimensional social capital in OBCs to elucidate antecedents of brand subjective well-being from the perspectives of social networks and relationships. Moreover, it examined how brands strategically expand their clientele base with regard to target customers.

The purpose of this paper is to investigate the influence of mobile internet (MI) use and risk factors on MI happiness.

An online survey with 521 MI users was conducted to test the direct and moderating effects of risk factors on MI happiness.

The results provide evidence that there is a non-linear relationship between variety of use and MI happiness, and consumers become happier with increased frequency of use. The results also indicate that the privacy risk and task risk reduce MI happiness, and both types of risks moderate the inverted U-shaped relationship between variety of use and MI happiness.

This study reconciles two opposing theories, stimulation vs displacement, on the impact of internet use on consumer well-being. The findings suggest that the stimulation effect of MI use is associated with an intermediate level of usage variety, while social displacement is more likely connected with higher- or lower-variety of use. Risk plays an important role in exploring the boundary conditions of both theories. The findings also have important implications to the debate over the role of privacy in consumer adoption of internet services or applications.

This study reconciles two opposing theories, stimulation vs displacement, on consumer happiness by elaborating the role of risk associated with MI use.

This paper aims to examine the effect of product market competition on firms’ unethical behavior (FUB) in the Chinese insurance industry and to further explore the boundary conditions of the main effects. On the basis of China’s commercial foundation, the study constructs a conceptual framework of FUB by drawing from the perspective of horizontal competition.

Data were collected from 52 property insurance firms at the branch level observed over the six-year period, 2011-2016. Within this framework, market power and market concentration were used to describe product market competition at firm and industry levels, respectively. The moderating effect of market munificence was analyzed to reveal the theoretical boundaries of the main effect. By drawing upon cost–benefit analysis and social network theory, the study used negative binomial model and Poisson model to quantitatively examine the relationship.

The relationship between product market competition and FUB is curvilinear. Especially at the firm level, market power exhibits a U-shape relationship with FUB; at the industry level, market concentration exhibits a U-shape relationship with FUB. In addition, market munificence positively moderates the impact of firm’s market power on FUB, whereas, market munificence negatively moderates the impact of industrial market concentration on FUB.

This paper explored a new type of unethical behavior that concerns consumers or the third party by emphasizing horizontal competitive contexts; it also provides a better understanding of the FUB–financial performance relationship from the perspective of competition. The moderating effects suggest that when the cause of FUB is different (market power vs market concentration), firms may make opposite ethical choice. However, the sample is from a single industry; it will be fruitful to further verify these findings in other industries such as the manufacturing sector. Moreover, the definition of FUB is confined to explicit forms such as participation or collusion but there is no way to measure the implicit forms of FUB.

First, the governance of FUB should not only focus on the firms themselves, but also take into account the industrial market structure. Second, proper use of governance measures for FUB can increase firms’ benefits from “compliance with the law”, enticing firms to decrease FUB. The third, firms with weak market positions, facing fierce competition, should not be involved in FUB for short-term benefit; indeed, a low-cost strategy can be adopted as the dominant competitive strategy. While, in cases of highly concentrated market structure, firms should strive to avoid involvement in FUB through collusion with other rivals.

As it is a very common phenomenon that firms in competitive relationships may adopt FUB toward third parties or consumers, this trend has become a hot topic in the economic and social development in China. The study’s conclusions reveal that a more proactive and ambitious ethical decision is desirable for all kinds of firms; moreover, firms should make a rational choice between “short-term interest” and “long-term survival”. When firms identify the compliance of business ethics as an opportunity to differentiate themselves and perceive the benefits of decreasing FUB as outweighing the costs, the level of FUB will be inhibited, and social welfare will increase.

The primary contribution of this research resides in identifying product market competition as a previously unexplored predictor of FUB, thus revealing the dark side of product market competition. In addition, nonlinear relationships between product market competition and FUB indicate that situations of competition exert an important influence on FUB both at the firm and industry level. This paper’s conclusion provides a more meticulous theoretical explanation for FUB. This research demonstrates that the traditional ethical framework is not sufficient to explain FUB in a horizontal competitive context. Indeed, resource constraints and competitive pressures should also be considered.

Consumers share negative brand experience in many occasions to vent their emotion and seek support. The purpose of this paper is to investigate the impact of negative sharing on members’ happiness in online brand communities by drawing from two opposing constructs: social support and social exclusion.

Both survey and experiment methods were employed to test the conceptual model. Online survey data were collected from 1,015 mobile internet users.

The findings reveal that negative sharing may enhance a sharer’s happiness through online social support particularly for novice community members. The findings also indicate greater online social exclusion for experienced members than for novice members. These findings cast doubt on the widely held assumption that increased engagement in a community will always produces positive outcomes. The moderating effect of membership duration is confirmed with an experiment of MI’s brand community members.

The study of happiness in online brand community sheds new light on consumer–brand and user–community relationships.

While most previous studies on negative sharing only explored the negative side of consequences, the authors contribute to this line of research by introducing both positive (social support) and negative (social exclusion) outcomes of negative reviews. The model also explains the conditions under which negative reviews enhance social support and social exclusion.

The purpose of this study is to offer explanations of the wide variation in the impact of market size on new market entry decisions – i.e. its positive impact lessens because of unreliable predictability of market size on post-entry profit and entry motivations other than post-entry profit.

On the basis of the two explanations, this paper builds a contingency frame that the impact of market size on new market entry depends on entry-context-specific variables. It validates the contingency frame, empirically analyzing 219 parameter estimates of the impact of market size on market entry obtained from 41 existing empirical studies.

The meta-analysis results reveal that the entry-context-specific variables used in this study – niche market entry, high-tech market entry, entry by industry incumbent firms and the year of market entry – notably moderate the impact of market size on new market entry decisions, as the research frame suggests.

This study examines the various literature and study outcomes in the areas of marketing, economics and strategy to elucidate whether and when market size is a critical driver of new market entry. In most cases, the greater the new market size, the greater is the propensity to enter the market. However, the contingency arguments stated in this paper suggest that firms may and do enter a new market even if the market size is not large at the time of entry.

This paper enhances the understanding of the relative importance of market size in market entry decisions, which depend on various entry contexts. It clarifies the direction and magnitude of the impact of such entry contexts.

We compare environmental impacts associated with incoming foreign direct investment versus domestic capital in China. We use aggregate data on Chinese provinces’ economic and pollution indicators to explore the effects of the financial origin of fixed capital. Our simultaneous models consider three prime channels through which these effects work: economic scale, sectoral composition, and pollution intensity. Results show that emissions associated with foreign financed capital are lower than with domestically financed capital for some but not all of the considered types of pollution.

This paper aims to contribute to the discussion of the following questions: How can the digital transition improve the management of the operation and maintenance of infrastructure in health-care facilities? What is the legacy for facility management (FM) teams in this post-COVID-19 management of hospital buildings?

Based on a literature review, this paper analyses and categorises existing research on the digital challenges for FM from 2011 until 2021 by conducting a qualitative and quantitative method of bibliometric analysis and discussing the status of digital transition impact on FM of the hospital buildings.

The trends and challenges of building information modelling, artificial intelligence and the Internet of Things identified and discussed in this paper aim to be as comprehensive as possible to grasp the situation of digital transition in the FM industry in the hospital buildings context. Regarding digital maturity, the limited number of publications highlights that control and management systems cannot fully manage the entire operational phase of hospital buildings. Giving intelligence to buildings will undoubtedly be the future. So making buildings reactive, interactive and immersive is an inevitable transformation for intelligent hospital building systems. Thus, the added value of digitalisation will help facility managers to overcome the issues pointed out in this paper to deal with the growing health demands and enable them to mitigate the impacts of a new and future pandemic.

The novelty of this paper is classifying and unifying facility managers' tendencies regarding high-level information management issues, which are lacking in the literature, with a focus on the approaches with potential and higher impact on FM in the hospital building context and the related steps that should be considered regarding data collection and data structures. These tendencies provide a set of new intelligent approaches and tools, which will increase the efficiency of processes, significantly impacting the potential of optimisation. Also, these trends can improve planning and management of scope, costs, environment and safety in the value chain of projects and assets, thus creating a more resilient and sustainable industry for facility managers in this post-COVID-19 management for hospital buildings.

Current research efforts exhibit a surge imperative for a building information modelling (BIM) approach that embodies a repository of all relevant data of existing building components while monitoring and consistently recording numerous components’ functions throughout its lifecycle, especially in Egypt. This research paper aims to develop an integrated as-is BIM-facility management (FM) information model for the existing building’s components via a case study, depicting a repository for historical data and knowledge amassed from inspections and conveying maintenance decisions automatically during the FM practices.

The developed approach pursues four successive steps: data acquisition and processing of building components; components recognition from point clouds; modelling scanned point clouds; and quick response code information transfer to BIM components.

The proposed approach incorporates the as-is BIM with the building components’ as-is FM information to portray a repository for historical data and knowledge collected from inspections to proactively benefit facility managers in simplifying, expediting and enhancing maintenance decisions automatically during FM practices.

This paper presents a digital alternative to manual maintenance recordkeeping concerning building components to retrieve their as-is and historical data using a case study in Egypt. This paper proposes a broad scan to as-is information BIM approach for the existing building’s components to condone maintenance interventions using a versatile, affordable, readily available and multi-functional method for scanning the building’s components using a handheld tool.

An interaction between emerging technologies (ETs) for facility management (FM) activities and stakeholder skills is necessary to promote the optimization of FM performance. Previous studies do not show strategies for the selection of ETs in FM considering the technological competencies of stakeholders. Thus, this study analyzes the interactions between ETs and FM from the perceptions of Brazilian professionals, identifying the most appropriate and effective technological solutions, based on a broad literature review.

The steps of the methodology are as follows: systematic literature review (SLR); detailing the ETs for FM; online questionnaire based on SLR findings; sample of Brazilian FM professionals; statistical treatment; and discussion.

Results indicate wireless sensor network, Internet of Thing, building information modeling and Big Data as ETs in FM with greater potential for optimization in the performance of FM activities, from survey respondents.

The scope of possible findings may have been biased, considering the small number of research participants and current transformations resulting from the COVID-19 pandemic (e.g. changes to standard operating procedures).

The results ensure greater security to facility managers in the effective implementation of ETs in FM activities.

The research explores the published studies and the consultation with Brazilian FM professionals in the selection of ETs.

Visual inspection and human judgement form the cornerstone of daily operations and maintenance (O&M) services activities carried out by facility managers nowadays. Recent advances in technologies such as building information modelling (BIM), distributed sensor networks, augmented reality (AR) technologies and digital twins present an immense opportunity to radically improve the way daily O&M is conducted. This paper aims to describe the development of an AR-supported automated environmental anomaly detection and fault isolation method to assist facility managers in addressing problems that affect building occupants’ thermal comfort.

The developed system focusses on the detection of environmental anomalies related to the thermal comfort of occupants within a building. The performance of three anomaly detection algorithms in terms of their ability to detect indoor temperature anomalies is compared. Based on the fault tree analysis (FTA), a decision-making tree is developed to assist facility management (FM) professionals in identifying corresponding failed assets according to the detected anomalous symptoms. The AR system facilitates easy maintenance by highlighting the failed assets hidden behind walls/ceilings on site to the maintenance personnel. The system can thus provide enhanced support to facility managers in their daily O&M activities such as inspection, recording, communication and verification.

Taking the indoor temperature inspection as an example, the case study demonstrates that the O&M management process can be improved using the proposed AR-enhanced inspection system. Comparative analysis of different anomaly detection algorithms reveals that the binary segmentation-based change point detection is effective and efficient in identifying temperature anomalies. The decision-making tree supported by FTA helps formalise the linkage between temperature issues and the corresponding failed assets. Finally, the AR-based model enhanced the maintenance process by visualising and highlighting the hidden failed assets to the maintenance personnel on site.

The originality lies in bringing together the advances in augmented reality, digital twins and data-driven decision-making to support the daily O&M management activities. In particular, the paper presents a novel binary segmentation-based change point detection for identifying temperature anomalous symptoms, a decision-making tree for matching the symptoms to the failed assets, and an AR system for visualising those assets with related information.