• An adaptive method for fish growth prediction with empirical knowledge extraction

      Li, Hui; Chen, Yingyi; Li, Wensheng; Wang, Qingbin; Duan, Yanqing; Chen, Tao; ; University of Surrey; China Agricultural University; Laizhou Mingbo Aquatic Products Co., Ltd; et al. (Elsevier, 2021-11-25)
      Fish growth prediction provides important information for optimising production in aquaculture. Fish usually exhibit different growth characteristics due to the variations in the environment, the equipment used in different fish workshops and inconsistent application by operators of empirical rules varying from one pond to another. To address this challenge, the aim of this study is to develop an adaptive fish growth prediction method in response to feeding decision. Firstly, the practical operational experience in historical feeding decisions for different fish weights is extracted to establish the feeding decision model. Then, a fish weight prediction model is established by regression analysis methods based on historical fish production data analysis. The feeding decision model is integrated as the input information of the fish weight prediction model to obtain fish weight prediction. Furthermore, an adaptive fish growth prediction strategy is proposed by continuously updating model parameters using new measurements to adapt to specific characteristics. The proposed adaptive fish growth prediction method with empirical knowledge extraction is evaluated by the collected production data of spotted knifejaw (Oplegnathus punctatus). The results show that established models can achieve a good balance between goodness-of-fit and model complexity, and the adaptive prediction method can adapt to specific fish pond’s characteristics and provide a more effective way to increase fish weight prediction accuracy. The proposed method provides an important contribution to achieving adaptive fish growth prediction in a real time from the view of aquaculture practice for spotted knifejaw.
    • Adoption of business analytics and impact on performance: a qualitative study in retail

      Ramanathan, Ramakrishnan; Philpott, Elly; Duan, Yanqing; Cao, Guangming; University of Bedfordshire (Taylor & Francis, 2017-07-11)
      This paper describes a qualitative study aimed at understanding issues faced by retail firms when they start a project of implementing Business Analytics (BA) and understanding the impact of BA implementation on business performance. Our study is informed by prior literature and the theoretical perspectives of the Technology-Organisation-Environment (TOE) framework but is not constrained by this theory. Using case studies of nine retailers in the UK, we have found support for the link between TOE elements and adoption. In addition, we have identified more interesting involvement of additional factors in ensuring how firms could maximise benefit derived from BA and traditional TOE factors that potentially could have additional impacts different from the ones. For example, there appears a link between adoption of BA and business performance (including performance in terms of environmental sustainability), and this link is moderated by the level of BA adoption, IT integration and trust.
    • The applicability of best value in the Nigerian public sector

      Bukoye, Oyegoke Teslim; Norrington, Peter; University of Bedfordshire (Taylor and Francis Inc., 2014-08-14)
      We examine the applicability of Best Value practices in the Nigerian public sector and present a Best Value Model for Nigeria. We find the literature does not extend to the Nigerian context. We make contributions towards understanding stakeholder perceptions of public service delivery best practice. We show Best Value as a significant initiative for improving public service delivery. The mixed methods survey reveals Nigerian Best Value initiatives do not exist significantly, but are applicable. Outcomes are exploration of a new area for Best Value application, incorporation of implementation issues into the model and the seven-stage process for its implementation. © Taylor & Francis Group, LLC.
    • Application of graphene-based materials for detection of nitrate and nitrite in water—a review

      Li, Daoliang; Wang, Tan; Li, Zhen; Xu, Xianbao; Wang, Cong; Duan, Yanqing; China Agricultural University; University of Bedfordshire (MDPI AG, 2019-12-20)
      Nitrite and nitrate are widely found in various water environments but the potential toxicity of nitrite and nitrate poses a great threat to human health. Recently, many methods have been developed to detect nitrate and nitrite in water. One of them is to use graphene-based materials. Graphene is a two-dimensional carbon nano-material with sp2 hybrid orbital, which has a large surface area and excellent conductivity and electron transfer ability. It is widely used for modifying electrodes for electrochemical sensors. Graphene based electrochemical sensors have the advantages of being low cost, effective and efficient for nitrite and nitrate detection. This paper reviews the application of graphene-based nanomaterials for electrochemical detection of nitrate and nitrite in water. The properties and advantages of the electrodes were modified by graphene, graphene oxide and reduced graphene oxide nanocomposite in the development of nitrite sensors are discussed in detail. Based on the review, the paper summarizes the working conditions and performance of different sensors, including working potential, pH, detection range, detection limit, sensitivity, reproducibility, repeatability and long-term stability. Furthermore, the challenges and suggestions for future research on the application of graphene-based nanocomposite electrochemical sensors for nitrite detection are also highlighted.
    • Applying blockchain technology to improve agri-food traceability: a review of development methods, benefits and challenges

      Feng, Huanhuan; Wang, Xiang; Duan, Yanqing; Zhang, Jian; Zhang, Xiaoshuan; University of Bedfordshire; China Agricultural University; Beijing Information Science and Technology University (Elsevier, 2020-03-11)
      Traceability plays a vital role in food quality and safety management. Traditional Internet of Things (IoT) traceability systems provide the feasible solutions for the quality monitoring and traceability of food supply chains. However, most of the IoT solutions rely on the centralized server-client paradigm that makes it difficult for consumers to acquire all transaction information and to track the origins of products. Blockchain is a cutting-edge technology that has great potential for improving traceability performance by providing security and full transparency. However, the benefits, challenges and development methods of blockchain-based food traceability systems are not yet fully explored in the current literature. Therefore, the main aim of this paper is to review the blockchain technology characteristics and functionalities, identify blockchain-based solutions for addressing food traceability concerns, highlight the benefits and challenges of blockchain-based traceability systems implementation, and help researchers and practitioners to apply blockchain technology based food traceability systems by proposing an architecture design framework and suitability application analysis flowchart of blockchain based food traceability systems. The results of this study contribute to better understanding and knowledge on how to improve the food traceability by developing and implementing blockchain-based traceability systems. The paper provides valuable information for researchers and practitioners on the use of blockchain-based food traceability management and has a positive effect on the improvement of food sustainability.
    • Artificial Intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy

      Dwivedi, Yogesh K.; Hughesa, Laurie; Ismagilova, Elvira; Aarts, Gert; Coombs, Crispin; Crick, Tom; Duan, Yanqing; Dwivedi, Rohita; Edwards, John; Eirug, Aled; et al. (Elsevier, 2019-08-27)
      As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial,intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision-making, engendering new opportunities for continued innovation. The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, realistic assessment of impact, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: business and management, government, public sector, and science and technology. This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.
    • Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda

      Duan, Yanqing; Edwards, John S.; Dwivedi, Yogesh Kumar; University of Bedfordshire; Aston University; Swansea University (Elsevier, 2019-02-07)
      Artificial intelligence (AI) has been in existence for over six decades and has experienced AI winters and springs. The rise of super computing power and Big Data technologies appear to have empowered AI in recent years. The new generation of AI is rapidly expanding and has again become an attractive topic for research. This paper aims to identify the challenges associated with the use and impact of revitalised AI based systems for decision making and offer a set of research propositions for information systems (IS) researchers. The paper first provides a view of the history of AI through the relevant papers published in the International Journal of Information Management (IJIM). It then discusses AI for decision making in general and the specific issues regarding the interaction and integration of AI to support or replace human decision makers in particular. To advance research on the use of AI for decision making in the era of Big Data, the paper offers twelve research propositions for IS researchers in terms of conceptual and theoretical development, AI technology-human interaction, and AI implementation.
    • Assessing the value of hotel online reviews to consumers

      Reino, Sofia; Massaro, Maria Rita; University of Bedfordshire (Springer, 2016-03-03)
      Previous research studied the impact of travel online reviews. However, this is quantitative and lacks of conceptual frameworks to ensure consistency. Only a few of these have considered influencing variables (i.e. characteristics of the review and the reader, and surrounding circumstances). Some of their findings are conflicting, which could relate to the lacking of a consistent approach. This study will only focus on online reviews about accommodation establishments. Its aim is to gain an understanding of the value of accommodation online reviews, through a qualitative study. A conceptual framework, based on consumer-perceived value theory, has been developed and face-to-face interviews with accommodation online review readers have been undertaken. The results suggest that the value of reviews is primary epistemic and partially functional, but limited emotional and social value has been reported. Furthermore, the elements eliciting the different value dimensions and additional variables influencing on their value (such as information search patterns) are identified.
    • Automatic recognition methods of fish feeding behavior in aquaculture: a review

      Li, Daoliang; Wang, Zhenhu; Wu, Suyuan; Miao, Zheng; Du, Ling; Duan, Yanqing; ; China Agricultural University; Renmin University of China; University of Bedfordshire (Elsevier, 2020-05-23)
      Feeding is a major factor that determines the production costs and water quality of aquaculture. Analysis of fish feeding behavior forms an important part of the feeding optimization. Fish feeding has generally been performed with automatic feeding machines which can lead to excessive or insufficient feeding. Recognition of fish feeding behavior can provide valuable input for optimizing feeding quantity. Due to the complexity of the environment and the uncertainty of fish behavior, the correlation and accuracy of behavior recognition are generally low. The accurate identification of fish feeding behavior till faces substantial challenges. This paper reviews the technical methods that have been used to identify fish feeding behavior in aquaculture over the past 30 years. The advantages and disadvantages of each method under different experimental conditions and applications are analyzed. Many methods are effective at evaluating and quantifying fish feeding intensity, but the recognition accuracy still needs further improvement. It is proposed by this paper that technologies such as data fusion and deep learning has great potential for improving the recognition of fish feeding behavior.
    • Block teaching as the basis for an innovative redesign of the PG suite of programmes in University of Bedfordshire Business School

      Kofinas, Alexander K.; Bentley, Yongmei; Minett-Smith, Cathy; University of Bedfordshire (Editorial Universitat Politècnica de València, 2017-12-31)
      This paper aims to provide a first evaluation of the University of Bedfordshire Business School’s innovative attempt to develop a new suite of Masters Programmes that delivers in terms of academic rigor and employability requirements while providing a rich student learning experience. The new delivery is based on a block delivery model that rationalises the previous offerings by providing a smaller range of standardized large units which are more tightly integrated to each other and are part of courses with particular characteristics such as a four-tier induction system (with inductions being progressively more employabilityfocused as students’ progress from one unit to the next) and the final capstone unit where students have a choice between a traditional dissertation and an experiential final project. That common architecture is coupled with a flipped classroom delivery style, utilization of blended learning and rich peer-to-peer learning opportunities with multiple entry points providing additional students into the cohorts for each unit. Preliminary data is provided here as an early evaluation of the approach’s effectiveness and efficiency in terms of the delivery experience, the assessment strategies, the levels of student engagement and performance, as well as the experience of staff and students.
    • Cabbalistic cases: demystifying generalizability

      Deigh, Linda; Farquhar, Jillian Dawes; London Metropolitan University; University of Bedfordshire (2015-07-01)
      Case study research is concerned with in-depth and within context knowledge which is generated empirically. As such it is well suited to address complex marketing problems thus advancing theory in the discipline. In spite of these benefits, case studies are rarely published in marketing journals thus depriving the discipline of rich insights and opportunities to build new theory. This relatively poor showing of case study research may be attributable to a perceived lack of rigour with one particular criticism being that case study findings are not generalizable. This paper sets out to investigate the generalizability ‘problem’ in case study research. It finds that strategic case selection and specificity in the bounding of cases enable the findings of a study to be extended to similar contexts and generalized to theory.
    • A conceptual framework of knowledge sharing for enhanced performance in the HEIs

      Khilji, Nasrallah; Duan, Yanqing; Tehrani, Jasmine; University of Bedfordshire (2020-12-31)
      Knowledge sharing is an essential management practice that provides a sustainable competitive advantage in a vibrant and dynamic economy (Kaur, 2019). To achieve an enhanced performance in the Higher Education Institutions (HEIs), it is essential to make sure that the teaching and learning system is determined by knowledge sharing approach (Nair and Munusami, 2019). The Higher Education Institutions are required to consider how they could better share knowledge from experts who have it to learners who need to get the best of such expertise (DarlingHammond et al., 2019). This study examines the knowledge sharing behaviour among academics and leaners in the HEIs by providing a better understanding for their enhanced performance. This is aimed to comprehend the individual acts of knowledge creation and the collective efforts of knowledge sharing adapted in the HEIs towards continuous improvement. A literature review is carried out to propose a conceptual framework of knowledge sharing for enhanced performance in the HEIs.
    • Corporate social responsibility: engaging the community

      Deigh, Linda; Farquhar, Jillian Dawes; Palazzo, Maria; Siano, Alfonso; University of Bedfordshire; London Metropolitan University; University of Salerno (Emerald, 2016-04-11)
      Purpose This paper aims to extend corporate social responsibility (CSR) theory by exploring how firms engage with community. The community is frequently cited as a stakeholder of the firm, but in spite of its status in networks it has not been the focus of research. Drawing on community theory and Carroll’s pyramid for the foundation of this study, the authors undertake an empirical investigation to advance knowledge in CSR engagement with a particular stakeholder group. Design/methodology/approach To generate an in-depth insight, the study adopts a multiple case study approach involving the purposeful selection of three retail banks in Ghana as units of analysis. It draws on multiple data sources to strengthen its findings Findings The study finds that community engagement consists of four spheres of activity: donations, employee voluntarism, projects and partnerships. Philanthropy forms part of largely ad hoc CSR actions by firms. The study also finds that philanthropy is not merely a desired function of the CSR pyramid but an essential one. Practical implications This research imparts increased understanding of how firms engage with an important but frequently overlooked stakeholder group – community. Originality/value This study presents specific theoretical extensions to CSR through its identification of four core activities of community engagement.
    • Data of the impact of aligning business, IT, and marketing strategies on firm performance

      Al-Surmi, Abdulrahman Mohamed; Cao, Guangming; Duan, Yanqing; University of Bedfordshire (Elsevier, 2019-10-15)
      The data presented in this article are related to the research article entitled “The Impact of Aligning Business, IT, and Marketing Strategies on Firm Performance” [https://www.sciencedirect.com/science/article/pii/S0019850118304449]. In order to succeed in today's competitive business environment, a firm should have a clear business strategy that is supported by other organizational strategies. While prior studies argue that strategic alignment enhances firm performance, either strategic alignment including multiple factors or strategic orientation of firms has received little attention. This study, drawing on contingency theory and configuration theory, investigates the performance impact of triadic strategic alignment among business, IT, and marketing strategies while simultaneously considers strategic orientation of firms. A research model is tested through SEM and MANOVA using data collected in a questionnaire survey of 242 Yemen managers. The findings indicate that (1) triadic strategic alignment has a positive impact on firm performance and (2) there is an ideal triadic strategic alignment for prospectors and defenders. This research contributes to strategic alignment literature and managers' understanding of how to align business, IT and marketing strategies to improve firm performance.
    • The debate on flexibility of environmental regulations, innovation capabilities and financial performance - a novel use of DEA

      Ramanathan, Ramakrishnan; Ramanathan, Usha; Bentley, Yongmei; University of Bedfordshire; Nottingham Trent University (Elsevier Ltd, 2017-03-27)
      Operational research models have been employed to understand development issues associated with environmental sustainability. This article describes a novel application of Data Envelopment Analysis (DEA) to help extend a specific debate in the literature on Porter’s hypothesis in environmental policy. The debate deals with the impact of flexibility of regulations on the relationship between innovation capabilities on financial performance in organisations. Using the resource based view of a firm, we hypothesise that relationship between innovation capabilities and financial performance in firms depends on how flexible or inflexible environmental regulations are. We apply DEA to capture the flexibility of environmental regulations. Our results indicate that innovation capabilities significantly influence financial performance of firms if firms feel that the environmental regulations they face are flexible and offer more freedom in meeting the requirements of regulations. On the other hand, corporations that feel that they face more inflexible regulations are not so effective in improving their financial performance with their innovation capabilities.
    • Designing an organization for innovation in emerging economies: the mediating role of readiness for innovation

      Arshi, Tahseen Anwer; Burns, Paul; Majan University College; University of Bedfordshire (Vilnius University Press, 2019-12-31)
      The study proposes an organizational design framework that impacts innovation in corporate firms. In an emerging economy like Oman, innovation helps to reduce the dependence on oil revenues and enhance its international competitiveness. However, the corporate organizations in emerging economies are unable to innovate effectively because they are not designed for innovation. Further, scarcity of resources undermines their readiness for innovation. This study empirically validates measures of an entrepreneurial organizational design framework in Omani corporate sector. In order to explain how a corporate organizational design promotes innovation and clarify the missing links between corporate entrepreneurial activity and innovation, the mediating role of readiness for innovation (RFI) is tested. Using a quantitative research approach, data is collected from 401 corporate firms in Oman and analysed using structural equation modelling. The findings support the proposition that entrepreneurial organizational design promotes both radical and incremental innovation degree and frequency, while RFI partially mediates the relationship between entrepreneurial inputs and innovation outputs. The study contributes to the understanding of innovation in emerging economies as it explains that RFI helps firms to enhance its innovation potential by optimizing its resources, capabilities and processes for innovation. These measures are essential for organizations, particularly in emerging economies focused on low cost innovation. The findings of the study will inform managerial decision-making in terms of designing organizations for innovation and implementation of measures related to readiness for innovation. PDF
    • Developing a conceptual framework for sustainable ‘last-mile’ delivery for Chinese online retailing market

      Zhang, Boyong; Bentley, Yongmei; University of Bedfordshire (Chartered Institute of Logistics and Transport UK, 2018-09-03)
      This study aims to develop a conceptual framework for sustainable last-mile delivery for China’s online retailing market via systematic literature review (SLR) and semi-structured interviews. Based on our SLR, European academia is the most productive and creative region regarding last-mile delivery research. Unfortunately, many projects and studies have failed or remained at preliminary stages. Nevertheless, European researchers and practitioners are very vigorous to implement new ideas into operations. They have introduced and developed different models, alternative solutions, new vehicles, regulatory suggestions, along with some inspiring frameworks and reviews. In the Chinese context, last-mile research remained at a theoretical level. Scholars are still trying to explain the relationship between e-commerce and last-mile delivery (Chen and Lin, 2013; Wang and Xiao, 2015), few have entered the innovative stage of research. Chinese scholars rarely mention terminologies such as sustainable last-mile, smart-cities, or smart logistics. They are in dire of need a roadmap which can provide guidance for last-mile decision-making process. ---
    • Developing a real-time monitoring traceability system for cold chain of Tricholoma matsutake

      Li, Xinwu; Yang, Lin; Duan, Yanqing; Wu, Zhigang; Zhang, Xiaoshuan; China Agricultural University; Tibet Agricultural and Animal Husbandry College; University of Bedfordshire (MDPI, 2019-04-11)
    • Development and evaluation of a brine mining equipment monitoring and control system using wireless sensor network and fuzzy logic

      He, Liu; Cui, Yan; Duan, Yanqing; Stankovski, Stevan; Zhang, Xiaoshuan; Zhang, Jian; China Agricultural University; University of Bedfordshire; University of Novi sad; Beijing Information Science & Technology University (SAGE, 2017-03-29)
      The brine mining equipment failure can seriously affect the productivity of the salt lake chemical industry. Traditional monitoring and controlling method mainly depends on manned patrol that is offline and ineffective. With the rapid advancement of information and communication technologies, it is possible to develop more efficient online systems that can automatically monitor and control the mining equipment and to prevent equipment damage from mechanical failure and unexpected interruptions with severe consequences. This paper describes a Wireless Monitoring and feedback fuzzy logic-based Control System (WMCS) for monitoring and controlling the brine well mining equipment. Based on the field investigations and requirement analysis, the WMCS is designed as a Wireless Sensors Network module, a feedback fuzzy logic controller, and a remote communication module together with database platform. The system was deployed in existing brine wells at demonstration area without any physical modification. The system test and evaluation results show that WMCS enables to track equipment performance and collect real-time data from the spot, provides decision support to help workers overhaul the equipment and follows the deployment of fuzzy control in conjunction with remote data logging. It proved that WMCS acts as a tool to improve management efficiency for mining equipment and underground brine resources.
    • Distributional characteristics of interday stock returns and their asymmetric conditional volatility: firm-level evidence

      Balaban, Ercan; Ozgen, Tolga; Girgin, Mehmet Sencer; University of Bedfordshire; Craig Associates, Edinburgh; TJK, Istanbul (Elsevier B.V., 2018-05-16)
      This paper is a pioneering effort to jointly analyze the characteristics of interday distributions of stock returns and their asymmetric time varying volatility using firm-level data in local currency from an emerging stock market, namely, the Bourse Istanbul, for the period January 1996 to December 2015. Using a modified Threshold Generalized Autoregressive Conditional Heteroscedasticity-in-Mean [TGARCH(1,1)-M] model; these distributional characteristics statistically assess in a unique framework (i) the weak-form informational efficiency based on the stylized facts of day of the week effects on stock returns and their conditional volatility; (ii) volatility persistence and asymmetry in conditional volatility; and (iii) the conditional total risk–return relationship, and the impact of systematic risk as an asset pricing factor. It is found that at firm level there are statistically significant positive or negative day of the week effects on either stock returns or their conditional volatility, or both. However, for a sample of 120 firms, a full and cross-sectional analysis of the interday distributions does not lead to a systematic pattern of return differences across days of the week. The average volatility is found to be highest on Mondays and the lowest on Wednesdays. It is reported that – as a proxy of total risk in a mean–variance framework – the estimated conditional standard deviation does not have a significant impact on stock returns for the great majority of the sample firms. With reference to the total risk–return relationship and the asymmetry in volatility, there are no significant differences between the industrial and financial sector companies. It is reported that the systematic risk is always priced; and the results are highly significant with a high explanatory power. Volatility is decidedly persistent for all firms investigated; while, a significant asymmetry in the conditional volatility cannot be reported for most of the firms. Contributing to the existing literature as a first time analysis of firm-level distributional characteristics of interday stock returns and their asymmetric conditional volatility with an additional proper risk-impact investigation, the empirical results are of importance primarily for asset pricing and risk management research and practice.