Search results

This study aims to focus on public policy concerning the implementation of public procurement policies in Nigeria and Ghana toward achieving value for money in the procurement of goods, services and works. It specifically analyzes some major administrative challenges Nigeria and Ghana are faced with in the administration/implementation of public procurement policies toward achieving value for money. It looks at the relationship between the state (regulatory authorities) and substate (procurement entities) in the public sectors of Nigeria and Ghana.

A comparative case study approach is adopted, where the two countries are compared in terms of achieving value for money. Data was collected from multiple sources, including in-depth interviews. The use of official documents and direct observations at the procurement regulatory authorities and entities’ premises.

This study found Nigeria often used the four Es – economy, efficiency, effectiveness and equity while Ghana mainly used the traditional five rights (right quantity, right quality, right price, right place and right time) as their criteria for ensuring value for money. The major administrative challenges found include corruption, low capacity of procurement personnel and poor knowledge of the procurement laws.

It recommends effective collaboration between government and civil society groups in the fight against corruption in procurement-related activities, with the implication that there is a need for periodic training for public procurement officials.

It adds to the field of public procurement in terms of value for money in the procurement of goods, services and works in developing countries context.

This study aims to examine hotel guests’ acceptance of technology agency – the extent to which they would let artificial intelligence (AI)-based systems make decisions for them when staying in hotels. The examination was conducted through the prism of several antecedents of acceptance of technology agency, including perceived ethics, benefits, risks and convenience orientation.

A thorough literature review provided the foundation of the structural model, which was tested using confirmatory factor analysis, followed by structural equation modeling. Data were collected from 400 US hotel guests.

The most important determinant of acceptance of technology agency was perceived ethics, followed by benefits. Risks of using AI-based systems to make decisions for consumers had a negative impact on acceptance of technology agency. In addition, perceived loss of competence and unpredictability had relatively strong impacts on risks.

The results provide a conceptual foundation for research on systems that make decisions for consumers. As AI is increasingly incorporated in the business models of hotel companies to make decisions, ensuring that the decisions are perceived as ethical and beneficial for consumers is critical to increase the utilization of such systems.

Most research on AI in hospitality is either conceptual or focuses on consumers’ intentions to stay in hotels that may be equipped with AI technologies. Occupying a unique position within the literature, this study discusses the first time AI-based systems that make decisions for consumers. The value of this study stems from the examination of the main concept of technology agency, which was never examined in hospitality.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

The effects of board composition on performance have long been discussed in management research using fractionalization measures. In this study, we propose an alternative measurement approach based on board polarization.

Using an exploratory analysis and applying the polarization measure to German Deutscher Aktienindex (DAX)-, Midcap-DAX (MDAX)- and Small Cap-Index (SDAX)-listed companies, this paper applies the polarization index to examine the relationship between board diversity and performance.

The results show that the polarization concept is well suited to measure principal-agent problems between the members of the management and supervisory boards. We reveal that board polarization is negatively associated with firm performance, as measured by return on investment (ROI).

This exploratory study shows that the measurement of board polarization can be linked to performance differences between companies, which offers promising starting points for further research.

Purpose of this study is to explore the nature of relationship between internationalization of firms, sustainability of their supply chains, and the extent of their green innovations. Understanding of the relationship between these constructs is important because of the ever increasing sustainability awareness of consumers in the leading economies of the world. This awareness is now compelling importers of goods from cheap-labor countries to ensure that their suppliers comply with sustainability regulations. This compliance becomes very challenging because of the lack of control on second-tier and third-tier suppliers in a supply chain. First-tier suppliers in this case may drive this effort but need to be motivated enough to do so. In case of environmental sustainability, green innovation (GI) may provide a gradual, and thus more affordable and practical, move toward more eco-friendly ways. As far as the motivation to commit to sustainability and GI is concerned, internationalization and export business expansion may act as one of the most effective motivators for these suppliers. However, the nature of relationship between these three constructs, i.e. internationalization of firms, sustainability of their supply chains and the extent of their GI requires a better understanding.

The work uses a novel data set collected from 146 medium and large textile firms operating in Pakistan. The partial least square-structural equation modeling approach is used for data analysis.

All three constructs of internationalization, GI and sustainable supply chain management (SSCM) are significantly associated and thus complement each other.

This work uses a novel agency theory perspective to analyze the relationship between internationalization, GI and SSCM. In that sense, the findings indicate that internationalization could be one of the incentives that can be used by the principals to deal with agents’ goal conflict and information asymmetry.

The information used for supervision by regulatory departments in public-private partnership (PPP) projects is primarily transmitted and processed by the PPP implementation department, which negatively impacts the information quality, leading to information asymmetry and undermining the overall effectiveness of supervision. This study aims to explore how to use blockchain to anchor the information used for supervision in PPP projects to the original information, to strengthen the oversight.

This paper adopts the principles of design science research (DSR) to design a conceptual framework that systematically organizes information along the information dissemination chain, ensuring the reliable anchoring of original information. Two-stage interviews involving experts from academia and industry are conducted, serving as formative and summative evaluations to guide the design.

The framework establishes a weak-centralized information organizing mode, including the design of governance community and on-chain and off-chain governance mechanisms. Feedback from experts is collected via interviews and the designed framework is thought to improve information used for supervision. Constructive suggestions are also collected and analyzed for further development.

This paper provides a novel example exploring the inspirations blockchain can bring to project governance, like exercising caution regarding the disorderly expansion of public sector authority in addressing information disadvantages and how to leverage blockchain to achieve this. Technical details conveyed by the framework deepen understanding of how blockchain benefits and the challenges faced in successful implementation for practitioners and policymakers. The targeted evaluation serves as rigorous validation, guiding experts to provide reliable feedback and richer insights by offering them a more cognitively convenient scenario.

As public–private partnerships (PPPs) have become preferred and veritable approach to deliver affordable housing, the seemingly lack of understanding of the significant factors that impact on success has become a notable setback. This study aims to delineate significant factors that can support decisions in affordable PPP public housing delivery.

Largely, a questionnaire survey was adopted to elicit insights from practitioners, policymakers and experts to develop an evaluative decision support model using an analytical hierarchy process and multi-attribute utility technique approach. Further, an expert illustration was conducted to evaluate and validate the results on the housing typologies.

The results revealed that energy efficiency and low-cost green building materials scored the highest weighting of all the criteria. Furthermore, multi-storey self-contained flats were found to be the most preferred housing typology and were significantly influenced by these factors. From the model evaluation, the scores on the factors of sustainability, affordability, cultural values and accountability were consistent across all typologies of housing whereas that of benchmarking, governance and transparency were varied.

The decision support factors captured varied dimensions of key factors that impact on affordable PPP housing that have not been considered in an integrated manner. These findings offer objective and systematic support to decision-making in affordable PPP housing delivery.

The purpose of this paper is to identify and prioritise supply chain finance (SCF) adoption enablers and develop a novel comprehensive framework to select supplier firms based on their SCF adoption capability.

The study deploys a three-phase method to identify and prioritise SCF adoption enablers, followed by developing a model to select suppliers according to their SCF adoption capability. An extensive literature review, followed by a Delphi approach-based expert interview, has been used to finalise the enablers. Using the Best Worst Method and the VIsekriterijumsko KOmpromisno Rangiranje technique, a supplier selection model has been developed in the context of a case company.

The financial health and technological advancement variables received the top priority, followed by collaborative efficiency, whereas the human resources and organisational variables received the slightest significance. A supplier selection framework has also been developed by using the adoption capability of these factors by the supplier partners. In this study’s model, Supplier 4 exhibited better SCF adoption capability and received the top priority.

Manufacturing supply chains in a developing country are the scope of the current study. Extensive future studies are required to derive a global consensus.

The proposed framework of this study can be used to select supplier firms based on their SCF adoption capability. Policymakers can emphasise the most critical enablers of SCF adoption to assist small supplier firms to be a part of the advanced global supply chains.

The current study established a novel comprehensive framework for supplier selection based on the Supply Chain Finance adoption capability of MSME supplier firms.

This paper aims to review empirical research on the relationship between institutional ownership (IO) and board governance (85 studies).

Based on agency and upper echelons theory, the heterogeneous monitoring function of specific types and the nature of institutional investors on board composition, compensation and chief executive officer (CEO) characteristics will be focused.

The author found that most studies have referred to archival studies, analyzed the impact of board governance on IO, focused on CEO characteristics, neglected IO heterogeneity and advanced regression models to address endogeneity concerns. In line with the theoretical framework, the relationship between total IO and board governance is heterogeneous. However, specific types such as foreign, dedicated and pressure-resistant institutions represent active monitoring tools and push for increased board governance.

The author provided useful recommendations for future research from a content and methodological perspective, e.g. the need for analyzing the impact of IO on sustainable board governance and other characteristics of top management team members, e.g. the chief financial officer.

As many regulatory bodies implemented regulations to promote shareholder rights and board governance, this literature review highlights the connections of both corporate governance mechanisms. Managers should conduct a careful and timely investor analysis and change the composition and compensation of the board of directors in line with institutional investors’ preferences.

This analysis makes useful contributions to prior research by focusing on IO and board governance, whereas the author structured the heterogeneous variables and results within the structured literature review. The authors guides researchers, regulatory bodies and business practice in this corporate governance topic.

Green technology innovation is the organic combination of green development and innovation driven. It is also a powerful guarantee for shaping sustainable competitive advantages of manufacturing enterprises. To explore what kind of executive incentive contracts can truly stimulate green technology innovation, this study aims to distinguish the equity incentive and reputation incentive, upon their contractual elements characteristics and green governance effects, and then put forward suggestions for green technology innovation accordingly.

This study establishes an evaluation model and uses empirical methods to test. Concretely, using data from A-share listed manufacturing companies for the period from 2007 to 2020, this study compares and analyzes the impact of equity and reputation incentive on green technology innovation and explores the relationship between internal green business behavior and external green in depth.

This study finds that reputation incentives focus on long-term and non-utilitarian orientation, which can promote green technology innovation in enterprises. While equity incentives, linked to performance indicators, have a inhibitory effect on green technology innovation. Internal and external institutional factors such as energy conservation measures, the “three wastes” management system, and environmental recognition play the regulatory role in the relationship between incentive contracts and green technology innovation.

Those findings validate and expand the efficient contracting hypothesis and the rent extraction hypothesis from the perspective of green technology innovation and provide useful implications for the design of green governance systems in manufacturing enterprises.