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In recent years, China has shifted its competitive strategy from competing on low cost to producing higher value added products and services, and the country has made the promotion of business excellence a national strategic priority. As a consequence, Chinese organizations need to know the factors that will make them world-class companies. Until recently, not much research has been done into these factors in the Chinese context. The few studies available unfortunately were mainly done only into specific elements of excellence and specific improvement techniques; a holistic and scientifically validated framework for creating high performance organizations (HPOs) cannot be found. The purpose of this study is to evaluate such a framework, which was quite recently developed, for the Chinese context.

A possible way forward is to use the HPO framework which was validated in earlier studies for the Asian context. In this paper, this research question is answered: Can the HPO framework be used to help Chinese organization to evaluate and improve the factors for excellence in the Chinese context? The study used a questionnaire which was distributed to respondents of a Chinese state-owned manufacturing enterprise. The results were discussed during a workshop to arrive at the main attention points for the organization.

The HPO framework was validated for the Chinese context and yielded valuable recommendations for improvement for the case company.

This study fills the gap which currently exists in empirical research about organization performance practices in Chinese. The study also has practical implications as management of Chinese state-owned enterprises, and possibly other Chinese companies, are now able to undertake focused improvement actions.

The purpose of this paper is to propose and apply a conceptual model that can be used to evaluate the functional performance of hospitality and tourism websites. This model will evaluate the websites from the perspective of information provision, communication, transactions, relationships, and technological merit, and how that applies to overall website functionality.

The paper uses a case study methodology in order to evaluate a random sample of the top 400 casual dining restaurant chains of 2007. The casual dining restaurant segment is chosen because of its importance in the overall foodservice industry, as well as its predominant use of websites.

Restaurant websites appear to be fairly strong in providing information in a technologically savvy environment. The areas that are found to be lower in functional efficiency are communication, relationship, and transaction. The three lowest‐rated individual attributes of the websites studied in the current research are the use and functionality of banners, reservations, and language on the websites.

As a case study, the limitations of this research are that the findings cannot be generalized to all restaurants because only a sample of casual dining chain restaurants is used. In addition, the model evaluated all of the components of the websites as being equal with the understanding that different website components weigh differently in their importance with consumers.

The implications of the paper are critical for website developers and hospitality organizations as the analysis shows that there is still a gap between customer perceptions of restaurant websites and the potential to use the website to engage and connect with guests. The paper will give industry practitioners some insight into the perceptions regarding the usability of their websites in order to allow the organizations to make changes accordingly.

The paper is pioneering in developing and proposing a conceptual model of website evaluation and applying this theory‐supported conceptual model to the casual dining chain restaurants website evaluation.

This study aims to construct mechanisms of big data-driven business model innovation from the market, strategic and economic perspectives and core logic of business model innovation.

The authors applied deductive reasoning and case analysis method on manufacturing firms in China to validate the mechanisms.

The authors have developed an integrated framework to deduce the elements of big data-driven business model innovation. The framework comprises three elements: perspectives, business model processes and big data-driven business model innovations. As we apply the framework on to three Chinese companies, it is evident that the mechanisms of business model innovation based on big data is a progressive and dynamic process.

The case sample is relatively small, which is a typical trade-off in qualitative research.

A robust infrastructure that seamlessly integrates internet of things, front-end customer systems and back-end production systems is pivotal for companies. The management has to ensure its organization structure, climate and human resources are well prepared for the transformation.

When provided with a convenient crowdsourcing platform to provide feedback and witness their suggestions being implemented, users are more likely to share insights about their use experience.

Extant studies of big data and business model innovation remain disparate. By adding a new dimension of intellectual and economic resource to the resource-based view, this paper posits an important link between big data and business model innovation. In addition, this study has contributed to the theoretical lens of value by contextualizing the value components of a business model and providing an integrated framework.

Although management scholars have embraced grand challenges research, in many cases, grand challenges have been treated as merely a context for exploring extant theoretical perspectives. By comparison, our approach – robust action – provides a novel theoretical framework for tackling grand challenges. In this invited article, we revisit our 2015 model, clarifying and elaborating its key elements and taking stock of subsequent developments. We then identify three promising directions for future research: scaffolding, future imaginaries, and distributed actorhood. Ultimately, our core message is remarkably simple: robust action strategies – participatory architecture, multivocal inscription and distributed experimentation – jointly provide a means for tackling grand challenges that is well matched to their complexities, uncertainties, and evaluativities.

Focuses on entrepreneurship in the fashion industry in Singapore, especially in the business of apparel fashion designing and retailing. Examines the factors that contribute to that success of this industry. Considers the support given to the fashion entrepreneur and the fashion schools in Singapore, including the difficulties encountered in starting and running such a business and the success factors. Concludes that the limited domestic market and lack of capital are the major difficulties. Suggests that whilst support has increased over the years, talent, the availability of capital and hard work seem to be the deciding factors determining success.

On its way to develop a smart grid in Indonesia, one key enabler in the early stage of implementation is advanced metering infrastructure (AMI). Thus, Perusahaan Listrik Negara (PLN), an electrical energy utility company owned by the government of the Republic of Indonesia as the only electricity utility company servicing customers from upstream to downstream in Indonesia, has started AMI program at some main cities. With AMI, real-time energy consumption profile, energy meter status and condition, and customer power quality can be acquired. Subsequently, these data collected by AMI can be used for further smart grid implementation by such IT systems and big data analysis. Instead of its function for smart grid backbone, AMI also significantly support smart energy on the city as a part of smart city initiatives. Nevertheless, its implementation requires more investment than the conventional metering system. This investment needs to be evaluated to define whether AMI is feasible and viable or not. This chapter is intended to observe the feasibility of AMI implementation in Indonesia using cost-benefit analysis (CBA). Two schemes were used as study objects, one scheme in which the communication infrastructure was managed by PLN itself, and the other one in which the communication infrastructure was managed by a third party. From the analysis, it appears that both schemes are proven to be feasible.

Fake news in cyberspace has greatly interfered with national governance, economic development and cultural communication, which has greatly increased the demand for fake news detection and intervention. At present, the recognition methods based on news content all lose part of the information to varying degrees. This paper proposes a lightweight content-based detection method to achieve early identification of false information with low computation costs.

The authors' research proposes a lightweight fake news detection framework for English text, including a new textual feature extraction method, specifically mapping English text and symbols to 0–255 using American Standard Code for Information Interchange (ASCII) codes, treating the completed sequence of numbers as the values of picture pixel points and using a computer vision model to detect them. The authors also compare the authors' framework with traditional word2vec, Glove, bidirectional encoder representations from transformers (BERT) and other methods.

The authors conduct experiments on the lightweight neural networks Ghostnet and Shufflenet, and the experimental results show that the authors' proposed framework outperforms the baseline in accuracy on both lightweight networks.

The authors' method does not rely on additional information from text data and can efficiently perform the fake news detection task with less computational resource consumption. In addition, the feature extraction method of this framework is relatively new and enlightening for text content-based classification detection, which can detect fake news in time at the early stage of fake news propagation.

The purpose of the paper is to present a case example of the power struggles and gender issues one daughter faced when she became a partner, and future successor, in the family business. This paper uses an ethnographic approach in order to study a small family farm in England. The case focuses on a small family farm, these businesses are unique in terms of their values and expectations for succession (Haberman and Danes, 2007), and identified by Wang (2010) as a fruitful avenue for research on daughter succession.

The empirical work was gathered through the use of a single site ethnographic case study involving participant observation as the researcher worked on the family farm and semi-structured interviews with family members over two years.

The results shed light on some of the social complexities of small family farms and power struggles within the family exacerbated by perceived gender issues. The work also highlights the potential threat to the daughter’s position as a partner, from her father’s favouritism of male employees.

Institutions that provide help to family farm businesses need to be aware of the potential power issues within the family specifically related to gender, particularly in terms of succession planning.

Using ethnography in family firms allows the researcher to be a part of the real-life world of family farmers, providing rich data to explore daughter succession.

Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

This study aims to investigate the complex relationship between corporate–nonprofit partnership characteristics (type, duration and source of communication); attitude toward the corporation (pretest and posttest); partnership evaluation; and stakeholders' willingness to engage in anti-corporate behaviors when a corporation behaves irresponsibly and negatively impacts an individual's community. The three partnership characteristics are evaluated, individually and collectively, to discern which, if any, characteristics protect or buffer a corporation from stakeholders' engagement in negative communication behaviors when controlling for how stakeholders evaluate the partnership and the corporation.

The study used an online experiment with 970 participants who were randomly assigned to a 2 × 2 × 3 × 2 factorial design.

Contrary to some previous research findings, this study found that individuals who evaluate either the corporation or the partnership favorably are more likely to engage in anti-corporate behaviors. Neither the partnership type nor communication source provides a buffering effect. The only partnership characteristic to generate a buffering effect was duration and that only occurred if the partnership lasted three years. This study concludes that when corporate social responsibility (CSR) and corporate social irresponsibility (CSI) co-occur, an amplification rather than mollifies stakeholders' willingness to enact anti-corporate communication behaviors in instances of CSI.

This study advances scholarly understanding of CSR and CSI as in-tandem concepts and practices. The findings challenge previous claims that corporate–nonprofit partnerships can buffer corporations from negative events. In contrast, we find that partnerships are limited in their ability to reduce stakeholders' willingness to engage in anti-corporate behaviors in instances of CSR. It also answers calls that CSR research should use non-fictitious companies to increase ecological validity of the study design.