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UK-China collaborative research programme “Advancing digital precision aquaculture in China (ADPAC)” [UK BBSRC grant BB/S020896/1 and Innovate UK grant 104904; National Key R&D Program of China, Grant no. 2017YFE0122100].

Retailers are facing challenges in making sense of the significant amount of data available for a better understanding of their customers. While retail analytics plays an increasingly important role in successful retailing management, comprehensive store segmentation based on Data Mining-based Retail Analytics is still an under-researched area. This study seeks to address this gap by developing a novel approach to segment the stores of retail chains based on 'purchasing behavior of customers' and applying it in a case study. The applicability and benefits of using Data Mining techniques to examine purchasing behavior and identify store segments are demonstrated in a case study of a global retail chain in Istanbul, Turkey. Over 600 K transaction data of a global grocery retailer are analyzed and 175 stores in Istanbul are successfully segmented into five segments. The results suggest that the proposed new retail analytics approach enables the retail chain to identify clusters of stores in different regions using all transaction data and advances our understanding of store segmentation at the store level. The proposed approach will provide the retail chain the opportunity to manage store clusters by making data-driven decisions in marketing, customer relationship management, supply chain management, inventory management and demand forecasting.

PurposeWhile marketing analytics can be used to improve organizational decision-making and performance significantly, little research exists to examine how the configurations of multiple conditions affect marketing analytics use. This study draws on configuration theory to investigate marketing analytics use in small and medium-sized enterprises (SMEs).Design/methodology/approachThis research employs a fuzzy-set qualitative comparative analysis using data collected from a survey of 187 managers in UK SMEs.FindingsThe key findings show that (1) configurations of multiple conditions provide alternative pathways to marketing analytics use, and (2) the configurations for small firms are different from those for medium-sized firms.Research limitations/implicationsThe research results are based on several key configurational factors and a single key-informant method to collect subjective data from UK SME managers.Practical implicationsThe study helps SMEs to understand that marketing analytics use is influenced by the interaction of multiple conditions, that there are alternative pathways to marketing analytics use, and that SMEs should choose the configuration that fits best with their organizational contexts.Originality/valueThe study contributes to the literature by addressing an important yet underresearched area, i.e. marketing analytics use in SMEs, applying a configurational approach to the research phenomenon. It highlights different pathways to marketing analytics use in SMEs. The findings provide empirical evidence on the possibility and implication of marketing analytics use being asymmetrical and different between small and medium-sized firms.

The desk rejection of submitted articles can be a hugely frustrating and demotivating process from the perspective of the researcher, but equally, a time-consuming and vital step in the process for the Editor, tasked with selecting appropriate articles that meet the required criteria for further review and scrutiny. The feedback from journal Editors within this editorial, highlights the significant gaps in understanding from many academics of the journal assessment process and acceptance criteria for progression to the review stage. This editorial offers a valuable “lived-in” perspective on the desk rejection process through the lens of the Editor, via the differing views of nine leading journal Editors. Each Editor articulates their own perspectives on the many reasons for desk rejection, offering key insight to researchers on how to align their submissions to the specific journal requirements and required quality criteria, whilst demonstrating relevance and contribution to theory and practice. This editorial develops a succinct summary of the key findings from the differing Editor perspectives, offering a timely contribution of significant value and benefit to academics and industry researchers alike.

While research underpinned by the resource-based view (RBV) appears to suggest that IT-enabled capabilities are positively linked to competitive advantage, such a link is often seen as a black box as the processes through which competitive advantage can be gained appears unclear. In particular, research appears to suggest that information processing capability is linked to decision-making effectiveness and competitive advantage; however, little research appears to examine the interrelationship among them. This study, drawing on the RBV, develops a mediation model to examine the link between competitive advantage and the key tenets of value, rarity, inimitability and non-substitutability of information processing capability in the context of business analytics; and whether this link is mediated through decision-making effectiveness. Based on data collected from 633 UK companies, this study shows that there is a positive link between the value, rarity and inimitability characteristics of information processing capability and competitive advantage, which is partially mediated by decision-making effectiveness. The findings contribute to the theoretical development of the RBV by developing a mediation model that looks inside the black box. They also contribute to managers’ knowledge and understanding of the mechanism through which the strategic value of information processing capability can be maximized.

Keywords: knowledge sharing, higher education, learning organization, training and development INTRODUCTION Knowledge sharing plays a vibrant role in the higher education institutions (HEIs) for enhanced performance, particularly through effective planning, organising, monitoring and coordinating the knowledge-based assets related to intellectual capital. [...]the HEIs would develop knowledge sharing mechanism for overall enhanced performance (Sanchis et al., 2020). [...]through using a profiling approach, this research paper is trying to highlight the most frequently researched elements of knowledge sharing in the higher education institutions. According to Burns and Griffith (2018), the technical information may be quantitative or qualitative, but is generally explicit and in the public domain. According to Marshall (2019) the HEIs' teaching and learning environment is required to embrace technology for knowledge sharing in order to develop variations in the fundamental principles of teaching and learning as far as the education sector performance is concerned.

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.

While marketing analytics plays an important role in generating insights from big data to improve marketing decision-making and firm competitiveness, few academic studies have investigated the mechanisms through which it can be used to achieve sustained competitive advantage. To close this gap, this study draws on the dynamic capability view to posit that a firm can attain sustained competitive advantage from its sensing, seizing and reconfiguring capabilities, which are manifested by the use of marketing analytics, marketing decision-making, and product development management. This study also examines the impact of the antecedents of marketing analytics use on marketing related processes. The analysis of a survey of 221 UK firm managers demonstrates: (a) the positive impact of marketing analytics use on both marketing decision-making and product development management; (b) the effect of the latter two on sustained competitive advantage; (c) the indirect effect of data availability on both marketing decision-making and production development management; and (d) the indirect effect of managerial support on marketing decision-making. The research model proposed in this study provides insights into how marketing analytics can be used to achieve sustained competitive advantage.

Advances in Business Analytics in the era of Big Data have provided unprecedented opportunities for organizations to innovate. With insights gained from Business Analytics, companies are able to develop new or improved products/services. However, few studies have investigated the mechanism through which Business Analytics contributes to a firm's innovation success. This research aims to address this gap by theoretically and empirically investigating the relationship between Business Analytics and innovation. To achieve this aim, absorptive capacity theory is used as a theoretical lens to inform the development of a research model. Absorptive capacity theory refers to a firm’s ability to recognize the value of new, external information, assimilate it and apply it to commercial ends. The research model covers the use of Business Analytics, environmental scanning, data-driven culture, innovation (new product newness and meaningfulness), and competitive advantage. The research model is tested through a questionnaire survey of 218 UK businesses. The results suggest that Business Analytics directly improves environmental scanning which in turn helps to enhance a company's innovation. Business Analytics also directly enhances data-driven culture that in turn impacts on environmental scanning. Data-driven culture plays another important role by moderating the effect of environmental scanning on new product meaningfulness. The findings demonstrate the positive impact of business analytics on innovation and the pivotal roles of environmental scanning and data-driven culture. Organizations wishing to realize the potential of Business Analytics thus need changes in both their external and internal focus.

Fish school feeding behavior analysis based on images can provide important information for aquaculture managers to make effective feeding decision. However, it is a challenging task due to intra-class variation, cross-occlusion, and unbalanced image categories in real high-density industrial farming. At present, most of the existing works on fish school feeding behavior are limited because they seem to ignored the spatial relationship between the region of interest in fish feeding images. To address this research gap, we propose a dual attention network with Efficientnet-B2 for fine-grained short-term feeding behavior analysis of fish school. The algorithm includes EfficientNet-B2 network and two parallel attention modules, which focus on the feature extraction of the feeding region. In addition, several training strategies, such as mish activation function, ranger optimizer, label smoothing, and cosine annealing, are employed to improve the algorithm performance. Especially, label smoothing technique is used to address the problem of image class imbalance. To evaluate the effectiveness of our method, performance of proposed algorithm is analyzed on fish school feeding behavior dataset and it is also compared with benchmark Convolutional Neural Networks (CNNs) including AlexNet, VGG, Inception, ResNet, Densenet, SENet, and MobileNet. Comprehensive experimental results show that proposed algorithm achieves very good results in terms of the accuracy (the test accuracy is 89.56% on datasets), precision, parameters and floating point operations per second (FLOPS), compared with the benchmark classification algorithm. Therefore, we proposed method can be integrated into aquacultual vision system to guide farmers to plan their feeding strategy.

Purpose Business analytics (BA) has attracted growing attention mainly due to the phenomena of big data. While studies suggest that BA positively affects organizational performance, there is a lack of academic research. The purpose of this paper, therefore, is to examine the extent to which top- and bottom-performing companies differ regarding their use and organizational facilitation of BA. Design/methodology/approach Hypotheses are developed drawing on the information processing view and contingency theory, and tested using multivariate analysis of variance to analyze data collected from 117 UK manufacture companies. Findings Top- and bottom-performing companies differ significantly in their use of BA, data-driven environment, and level of fit between BA and data-drain environment. Practical implications Extensive use of BA and data-driven decisions will lead to superior firm performance. Companies wishing to use BA to improve decision making and performance need to develop relevant analytical strategy to guide BA activities and design its structure and business processes to embed BA activities. Originality/value This study provides useful management insights into the effective use of BA for improving organizational performance.

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 U.K, 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.

There is a lack of understanding on the factors affecting active participation in business-to-business (B2B) online communities (OCs). To address this gap, we developed a model based on two theories: social exchange theory and the information systems success model. The model was validated by using survey data collected from 40 B2B discussion forums on LinkedIn (n=521). Our work made several significant contributions including an integrated model of factors affecting active participation in B2B OCs and a new validated measure for active participation. Further, we proposed several guidelines that assist B2B OC providers in building and maintaining successful communities.

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.

This research aims to identify and understand the contemporary practice of using Business Analytics (BA) in improving the performance of logistics companies by conducting exploratory case studies. We present seven case studies using a within-case and cross-case analysis of the practice of BA use in UK logistics firms. We position our analysis under major BA application areas identified in previous third-party logistics surveys. Based on an in-depth analysis, we present a Value-Adding Input-Output (VAIO) framework to support an understanding of the use of Business Analytics in logistics companies. One of the main findings is the recognition of four antecedents (skills, systems, technology, and trust issues) before deriving value from business analytics investments. When the antecedents are in place, it is possible for logistics companies to derive value by engaging in BA application areas. The value dimensions ultimately help logistics firms to be competitive in the market place. The framework supports the applicability of the Resource-Based View of a firm for BA use in logistics. The framework developed in this chapter provides a practical basis for logistics companies to derive value from their investments in Business Analytics. The Value-Adding Process Framework is a new framework suggested in this chapter.

Over the last three decades, China’s agriculture sector has been transformed from the traditional to modern practice through the effective deployment of Information and Communication Technologies (ICTs). Information processing and dissemination have played a critical role in this transformation process. Many studies in relation to agriculture information services have been conducted in China, but few of them have attempted to provide a comprehensive review and analysis of different information dissemination models and their applications. This paper aims to review and identify the ICT based information dissemination models in China and to share the knowledge and experience in applying emerging ICTs in disseminating agriculture information to farmers and farm communities to improve productivity and economic, social and environmental sustainability. The paper reviews and analyzes the development stages of China’s agricultural information dissemination systems and different mechanisms for agricultural information service development and operations. Seven ICT-based information dissemination models are identified and discussed. Success cases are presented. The findings provide a useful direction for researchers and practitioners in developing future ICT based information dissemination systems. It is hoped that this paper will also help other developing countries to learn from China’s experience and best practice in their endeavor of applying emerging ICTs in agriculture information dissemination and knowledge transfer.

The COVID-19 pandemic has forced many organisations to undergo significant transformation, rethinking key elements of their business processes and use of technology to maintain operations whilst adhering to a changing landscape of guidelines and new procedures. This study offers a collective insight to many of the key issues and underlying complexities affecting organisations and society from COVID-19, through an information systems and technological perspective. The views of 12 invited subject experts are collated and analysed where each articulate their individual perspectives relating to: online learning, digital strategy, artificial intelligence, information management, social interaction, cyber security, big data, blockchain, privacy, mobile technology and strategy through the lens of the current crisis and impact on these specific areas. The expert perspectives offer timely insight to the range of topics, identifying key issues and recommendations for theory and practice.

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.

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.

The number of users of well-known e-commerce websites such as Taobao, Jingdong, and Amazon has exceeded one billion. This means that the information provided by these and similar websites which is growing very fast, could be a valuable source of support for decision making, if discovered. All kinds of data derived from e-commerce websites must be managed and analyzed in order for them to remain competitive and to prevent reduced satisfaction or interest of customers. Business Analytics and Big Data Analytics are methodologies that can discover valuable insight hidden in data. In this paper, recent studies on e-commerce and Business Analytics or Big Data Analytics published within the last five years will be surveyed to discover what kind of business value is created with usage of analytics in these studies. This investigation also has the potential to find research gaps and direct future research.

Purpose This paper aims to understand the key factors affecting collaborative innovation in a destination management organisation from a dynamic capability perspective. Design/methodology/approach An in-depth case study was conducted using semi-structured interviews with the CEO and Chairman of the destination management organisation (DMO) and internal DMO documents from 2011 to 2016. Thematic analysis was carried out on the data both deductively, with generic themes identified and informed by theory, and inductively, where detailed subthemes were developed from the data. Findings The success of innovation in the context of a DMO depends on having a strong base of microfoundations that underpin the DMO’s capabilities to sense and seize opportunities and reconfigure its assets for competitive advantage. Collaboration with the key players in the sector has been the essential elements of these microfoundations. Research limitations/implications This study has been conducted within a single DMO case study. Future research should test the proposed models in different types of organisations and collaborative contexts. Practical implications The proposed dynamic capability framework helps managers achieve collaborative innovation, leading to competitive advantage through better development of relevant capabilities. Originality/value The study represents a first attempt to understand the key factors enabling successful collaborative innovation in the context of DMOs, from a dynamic capability perspective. The unique opportunity of accessing information and witnessing the changes in a DMO over a period of five years enabled the authors to gain in-depth insights and comprehensive understanding as to why and how a UK DMO has been successful in enhancing its business performance through a successful collaborative innovation.

While business analytics is being increasingly used to gain data-driven insights to support decision making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness (DME) at the organizational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organizational DME. The research model is tested using structural equation modeling based on 740 responses collected from U.K. businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capability, which in turn has a positive effect on DME. The findings also demonstrate that the paths from business analytics to DME have no statistical differences between large and medium companies, but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision making. They also contribute to managers’ knowledge and understanding by demonstrating how business analytics should be implemented to improve DME.

Purpose – The objective of this paper is to address the question whether and how firms can follow a standard management process to cope with emerging corporate social responsibility (CSR) challenges? Both researchers and practitioners have paid increasing attention to the question because of the rapidly evolving CSR expectations of stakeholders and the limited diffusion of CSR standardization. The question was addressed by developing a theoretical framework to explain how dynamic capabilities can contribute to effective CSR management. Design/methodology/approach – Based on 64 world-leading companies’ contemporary CSR reports, we carried out a large-scale content analysis to identify and examine the common organizational processes involved in CSR management and the dynamic capabilities underpinning those management processes. Findings – Drawing on the dynamic capabilities perspective, we demonstrate how the deployment of three dynamic capabilities for CSR management, namely, scanning, sensing and reconfiguration capabilities can help firms to meet emerging CSR requirements by following a set of common management processes. The findings demonstrate that what is more important in CSR standardization is the identification and development of the underlying dynamic capabilities and the related organizational processes and routines, rather than the detailed operational activities. Originality/value – Our study is an early attempt to examine the fundamental organizational capabilities and processes involved in CSR management from the dynamic capabilities perspective. Our research findings contribute to CSR standardization literature by providing a new theoretical perspective to better understand the capabilities enabling common CSR management processes.

Classification simulation using SVM, fuzzy SVM, and FKP-MCOC classifiers. An improved FKP-MCO classifier based on fuzzification method, kernel technique, and penalty factors is proposed and is used for predicting protein-protein interaction hot spots.A fuzzy contribution of each input point is introduced to MCO classifier for soft separation.The penalty factors are used to trade-off overfitting for the majority and underfitting for the minority in dataset.FKP-MCOC avoids solving the quadratic programming problem so as to gain efficiency.FKP-MCOC obtains better performance of predicting active compounds in bioassay and protein interaction hot spots than MCOC and other classifiers in stability, separation and generalization. In order to understand the patterns of various biological processes and discover the principles of protein-protein interactions (PPI), it is important to develop effective methods for identifying and predicting PPI and their hot spots accurately. As for multi-criteria optimization classifier (MCOC), it can learn a decision function from different classes of training data and use it to predict the class labels of unknown samples. In many real world applications, owing to noises, outliers, imbalanced class distribution, nonlinearly separable problems, and other uncertainties, the predictive performance of MCOC degenerates rapidly. In this paper, we introduce a fuzzy contribution to each instance of training data, the unequal penalty factors to the samples in imbalanced classes, and kernel method to nonlinearly separable dataset, then a novel multi-criteria optimization classifier with fuzzification, kernel and penalty factors (FKP-MCOC) is constructed so as to reduce the effects of anomalies, improve the class imbalanced performance, and nonlinear separability in classification. The experimental results of predicting active compounds and protein interaction hot spots and comparison with MCOC, support vector machines (SVM) and fuzzy SVM, the conclusion shows that FKP-MCOC significantly increases the efficiency of classification, the partition of active and inactive compounds in bioassay, the separation of hot spot residues and energetically unimportant residues in protein interactions, and the generalization of predicting active compounds and hot spot residues in new instances.

Purpose – This paper aims to advance information and communication technologies (ICT) adoption research and practice by examining and understanding the emerging ICT adoption in small and medium enterprises (SMEs) from a dynamic process perspective using actor-network theory (ANT). Design/methodology/approach – This study employs a qualitative approach to investigate how services SMEs are constantly engaging in ICT adoption for improving business performance. Two rounds of interviews were conducted with 26 interviewees. Data collected from the unstructured and semi-structured interviews were analysed to understand the dynamic adoption process, actors involved and their interactions. Findings – The findings reveal the recursive and dynamic nature of the emerging ICT adoption process and the constant interactions and negotiations of various actors. Underpinned by the key concepts of ANT and validated by the empirical data, a framework is developed to depict the stages of dynamic process of emerging ICT adoption, the actors involved and the associated key activities. Research limitations/implications – Qualitative research is interpretive in nature and the size of the sample used is limited. These limitations require caution for the generalization of the findings. The framework can be further validated across a wider population using mixed methods combining qualitative and quantitative approaches. Practical implications – Emerging ICT adoption has moved from a simple adopters’ participation process to involving various actors that constantly interact and influence the process. SMEs manager can be influenced by and influence the technology advancement. As a result, SMEs need constantly interact with various human and non-human actors to keep up with the new ICT development and benefit from the emerging opportunities. Originality/value – The research focuses on the emerging ICT adoption in SMEs from the dynamic process perspective using ANT. It advances ICT adoption research and practice by developing a framework to depict the dynamic and interactive nature of ICT adoption process, and the actors involved and their interactions in the adoption process.

Tricholoma matsutake (T. matsutake) is a special type of fungus known as "the king of bacteria", and has the very high economic value. However, it is also very difficult to transport due to its corruptibility. Therefore, tracing and tracking the quality and safety of T. matsutake in the cold chain is very important and necessary. Based on changes in the cold chain environmental parameters determine the safety of T. matsutake is a viable option. This paper developed and tested a real-time monitoring traceability system (RM-TM) using emerging Internet of Things (IoT) technologies for monitoring the cold chain logistics environmental parameters of T. matsutake. Finally, system testing and evaluation have shown that RM-TM can track and monitor temperature, humidity, oxygen and carbon dioxide fluctuations in the cold chain in real-time. In addition, the collected data can be used to increase the transparency of cold chain logistics and to more effectively control quality, safety, and traceability. In general, the system evaluation results show that it is reliable and meets the requirements of users.

Purpose – Differences in corporate commitments to sustainability have attracted increasing attentions of both researchers and practitioners. However, reasons behind such differences still lack a generic theorization. We propose that one source of these differences lies in the development and application of what we refer to as dynamic capabilities for corporate sustainability within the firm. Drawing on the dynamic capabilities view, the objective of this paper is to examine the fundamental role of dynamic capabilities in corporate sustainable development. Design/methodology/approach – The research developed a framework of dynamic capabilities for corporate sustainability and used the approach of content analysis to verify the framework based on the CSR reports of UK leading companies. Findings – The research demonstrates that the dynamic capabilities for corporate sustainability enable firms to monitor the emerging sustainability needs of various stakeholders, seize sustainable development opportunities f...

Using fuzzy-set qualitative comparative analysis (fsQCA), this study investigates the conditions leading to a higher level of innovation. More specifically, the study explores the impact of inter-organisational knowledge transfer networks and organisations' internal capabilities on different types of innovation in Small to Medium size Enterprises (SMEs) in the high-tech sector. A survey instrument was used to collect data from a sample of UK SMEs. The findings show that although individual factors are important, there is no need for a company to perform well in all the areas. The fsQCA, which enables the examination of the impacts of different combinations of factors, reveals that there are a number of paths to achieve better incremental and radical innovation performance. Companies need to choose the one that is closest to their abilities and fits best with their resources.

This article reports on the application of Research-Informed Curriculum Design (RICD) for the development and implementation of an MSc Program in Project Management. The research focused on contemporary issues in project management and provided an analysis of project management approaches, tools, and techniques currently used in organizations. Research methods included a literature review, questionnaire survey, focus group studies, and in-depth interviews with project managers. The research findings led to better understanding of current practice from project managers’ perspectives and informed the curriculum design of the program. Feedback was obtained from external examiners, project managers, alumni, and current students. Evaluation indicates that the RICD approach has produced a successful program and ensured it is relevant to industry and vocationally attractive to students.

Dynamic scanning, identification, and reconfiguration capabilities can facilitate firms' strategic change toward sustainability and higher competitive advantage in an evolving market environment.

According to Simon's (1977) decision making theory, intelligence is the first and most important phase in the decision making process. With the escalation of information resources available to business executives, it is becoming imperative to explore the potential and challenges of using agent-based systems to support the intelligence phase of decision-making. This research examines UK executives' perceptions of using agent-based support systems and the criteria for design and development of their ''ideal'' intelligent software agents. The study adopted an inductive approach using focus groups to generate a preliminary set of design criteria of ''ideal'' agents. It then followed a deductive approach using semi-structured interviews to validate and enhance the criteria. This qualitative research has generated unique insights into executives' perceptions of the design and use of agent-based support systems. The systematic content analysis of qualitative data led to the proposal and validation of design criteria at three levels. The findings revealed the most desirable criteria for agent based support systems from the end users' point view. The design criteria can be used not only to guide intelligent agent system design but also system evaluation.

The learner’s acceptance of e-learning systems has received extensive attention in prior studies, but how their experience of using e-learning systems impacts on their behavioural intention to reuse those systems has attracted limited research. As the applications of e-learning are still gaining momentum in developing countries, such as China, it is necessary to examine the relationships between e-learners’ experience and perceptions and their behavioural intention to reuse, because it is argued that system reuse is an important indicator of the system’s success. Therefore, a better understanding of the multiple factors affecting the e-learner’s intention to reuse could help e-learning system researchers and providers to develop more effective and acceptable e-learning systems. Underpinned by the information system success model, technology acceptance model and self-efficacy theory, a theoretical framework was developed to investigate the learner’s behavioural intention to reuse e-learning systems. A total of 280 e-learners were surveyed to validate the measurements and proposed research model. The results demonstrated that e-learning service quality, course quality, perceived usefulness, perceived ease of use and self-efficacy had direct effects on users’ behavioural intention to reuse. System functionality and system response have an indirect effect, but system interactivity had no significant effect. Furthermore, self-efficacy affected perceived ease of use that positively influenced perceived usefulness.

Using intelligent agent-based systems to support information processing for executives has not been significantly advanced in both theory and practice. Research into this field tends to focus more on technical aspects than on social perspective. When executives are faced with increasing information availability and uncertainty in the business environment, using intelligent agent-based systems to enhance executives' information processing capability appears both an opportunity and a necessity. This study examines UK executives' perceptions of intelligent agent-based systems for information scanning, filtering, interpretation and alerting. The study follows a deductive research design, i.e. hypothesis formulation and testing from the user's perspective. Qualitative data was collected through focus groups and interviews with executives in the UK. The study produces rich evidence that challenges preconceptions of using agent-based information processing system by executives. The findings develop insight into executives' behavior in information processing, which has implications for intelligent system developers and organizational information processing practice.

Expert systems (ESs) were introduced more than two decades ago, but their effectiveness and success are still in debate. This paper attempts to make a contribution to the better understanding of ES applications from a knowledge transfer perspective. This paper argues that an ES application is knowledge transfer that uses Information and Communication Technologies (ICT). Underpinned by knowledge transfer theories and through a series of empirical investigations of ES projects in agriculture, this study recognises the importance of human interactions in the ESs implementation process. Based on the evidence collected, a number of key players are examined. They are knowledge provider/sender, knowledge engineer, knowledge extensionist and knowledge recipient. This paper represents a first attempt to acknowledge the role of a knowledge extensionist in the ICT-based knowledge transfer process. The name ‘extensionist’ is borrowed from earlier literature and describes an actor whose role is an intermediary in supporting transferring knowledge towards the knowledge user. Findings demonstrate the significant contributions made by extensionists towards the success of ESs applications. It is argued that the rigidity and limitations of ESs in ICT-based knowledge transfer can be significantly reduced with the involvement of close human interactions with the knowledge recipient.

This paper reports research findings from a project funded by the European Commission. The research used case studies and surveys to identify gaps between Europe and China in the level of Internet adoption in fresh-produce supply chains. The project reveals barriers to Internet adoption in China in this industry, and employs a transnational knowledge transfer approach to reduce these barriers. In a wider context, the paper analyses the features involved in this knowledge transfer from a knowledge management perspective. Specifically, it outlines the main activities, key actors and the transfer stages involved. The insights gained help further our understanding of knowledge transfer in transnational contexts. The implications of these findings for academia, managers and policy makers are summarized.

References  Citations Metrics  Reprints & Permissions  PDF Abstract The rapid growth and new development of internet technologies have provided many significant opportunities for cost reduction and service improvement for the supply chain. However, the adoption of the internet technologies in agribusiness supply chains (SC), especially the fresh produce supply chain, is still slow and far behind other sectors. This paper is about the EU funded project VEGNET (Enhancing Vegetable Supply Chain Management with Internet Technologies) which aims to accelerate the speed of internet adoption among fresh produce supply chains involving small‐ and medium‐sized enterprises (SMEs). The paper first introduces the project's objectives and approaches. It then presents some key findings from a survey conducted with United Kingdom SMEs in fresh produce supply chains. These findings provide actual insights into the current internet and software usage of the United Kingdom SMEs and help to reveal gaps between Europe and China. Findings and implications from the project's other activities, such as case studies and surveys in China are also discussed.

The lack of anticipated engagement in e-business by Small and Medium sized Enterprises (SMEs) is a rising concern to the UK government and service providers alike. This article is based on the e-adoption model to examine the current practice of e-business technology adoption in SMEs and the driving forces for and against the adoption. Through interviews with 40 owner managers in the electronic components industry, the article reveals that most of the small firms in this industry are at the lower level of the “e-adoption ladder”—predominantly using the Internet and e-mail. SMEs in this industry have not yet widely engaged in online transactions. The current level of adoption is driven by both internal and external factors, including operational benefits, industry common practice, and peer pressure. External forces such as a lack of push from suppliers and customers and a lack of strategic vision of using advanced e-business technology for competitive advantages have determinant effects on the level and scale of e-adoption in SME sector. The e-adoption ladder model is modified by incorporating the influential factors identified within this study. The findings have many implications for researchers, service providers, and policy makers.

International audience; Agriculture is a knowledge intensive sector. Information and knowledge plays an essential role in helping farmers to improve productivity and sustainability through promoting and adopting the most effective and relevant innovations and technologies. With rapid development and advances in agricultural science and technology, traditional agriculture practices have been transformed to knowledge based and digital agriculture production. This paper reports a project that aims to improve the agricultural information and knowledge flow in Cambodia by adopting China’s success in using Mobile Internet Technologies. The paper provides a brief review of China’s current achievements in using ICTs to accelerate information and knowledge flow in Agriculture and Cambodia’s current status in using ICT for agriculture information disseminations. An empirical investigation was carried out in Cambodia to gain more insights into the farmers information needs and their intention to adopt Mobile Internet based information dissemination services. Based on the empirical study, Chinese experience in using Mobile App was introduced and a mobile App called AgriApp was designed and tailored to meet the Cambodia’s needs and conditions. This AgriApp was initially tested and valuable feedback was collected for improvement and better deployment in Cambodia.

PurposeExternal knowledge is generally believed to be of prime importance to small to medium‐sized enterprises (SMEs). However, a review of the literature shows that no empirical research has looked at knowledge management issues at the inter‐organizational level in SMEs. This paper seeks to report on an empirical investigation with UK SMEs in the service sector to identify their needs and practices regarding inter‐organizational knowledge transfer, and thus provide empirical evidence to support the above belief.Design/methodology/approachA two‐tier methodology (i.e. using both questionnaire survey and interview approaches) is deployed to address the main research objectives. A questionnaire survey of SMEs is carried out to investigate their current inter‐organizational knowledge transfer situation and managers' perception on various relevant issues. Then 12 face‐to‐face interviews with SME managers are conducted to further validate key findings drawn from the questionnaire survey.FindingsThe empirical evidence collected from the survey and interviews confirms the general belief that external knowledge is of prime importance for SMEs, and demonstrates that SMEs have very strong needs for external knowledge and inter‐organizational knowledge transfer.Research limitations/implicationsThe findings provide very strong underpinning for further theoretical research on inter‐organizational knowledge transfer in SMEs. However, this study has certain limitations: its results may not be applicable to other industrial sectors or the same sector in other countries; or to micro or large companies; nor does it involve cross‐cultural issues.Originality/valueBy adopting a two‐tier research methodology, this study provides more reliable understanding and knowledge on SMEs' inter‐organizational knowledge transfer needs and practices, and fills the gap that exists in the empirical investigations on the subject.

Adoption of IT innovations is attracting increasing attention. Researchers are particularly interested in factors that affect the adoption of IS and IT innovations. Innovation diffusion theory is used frequently to evaluate the effect of perceived innovation attributes and the adoption of innovations. Nevertheless, explanatory power of perceived innovation attributes varies across different innovations. Given the importance of online e-payment to the further development of e-commerce and its importance as a payment innovation, this research examines the adoption of online e-payment by business enterprises using Rogers’ relational model of perceived innovation attributes and rate of adoption. The findings indicate that only perceived compatibility has significant influence on online e-payment adoption of Chinese companies. It is hoped that this research can help other researchers with related statistical procedures and analytical steps in their study of IS/IT adoption using innovation diffusion theory.

Convergence of technologies in the Internet and the field of expert systems have offered new ways of sharing and distributing knowledge. However, there has been a general lack of research in the area of web-based expert systems (ES). This paper addresses the issues associated with the design, development, and use of web-based ES from a standpoint of the benefits and challenges of developing and using them. The original theory and concepts in conventional ES were reviewed and a knowledge engineering framework for developing them was revisited. The study considered three web-based ES: WITS-advisor -- for e-business strategy development, Fish-Expert -- for fish disease diagnosis, and IMIS -- to promote intelligent interviews. The benefits and challenges in developing and using ES are discussed by comparing them with traditional standalone systems from development and application perspectives.

This paper presents a research attempt to develop and evaluate a Web-based tele-diagnosis system for fish diseases. Fish disease diagnosis is a complicated process and requires high level of expertise. A tele-diagnosis system T-VET is being developed and tested in China. T-VET is the key sub system of a Web-based expert system for fish disease diagnosis. This paper looks at why a tele-diagnosis system is needed and what are the advantages and difficulties in developing and using such a system. The system's architecture and components are described. A user-centered approach was adopted throughout the development process to ensure the system would meet users' needs and will be accepted. As a result, the system functions were emerged and improved by users' requirements. The experience and feedback from testing and evaluating the system with potential users are discussed. Some valuable insights into the use of the Internet as a tele-diagnosis tool in aquaculture are highlighted.

Business environment scanning contributes a great deal to strategic intelligence gathering. However, earlier studies treat the business environment as a single entity. This study based on a multi-industry survey examined how UK executives perceive the stability of the business environment in which their companies operate, and what environmental sectors are perceived more strategically important than others for information scanning. The effort reveals that UK executives perceive the immediate-task environment information more strategically important than far-general environment information, but the perception of far environment information differs widely from industry to industry. A corporate "radar" system for business environment scanning is proposed to offer practical guidance. Our conclusion is that industry-specific environment sectors should be identified for strategic information scanning.

This study draws on relevant literature from Europe and the USA to show that there have been a number of reported failures of Executive Information Systems (EISs) in practice over the last decade. Design concerns, such as data access, ease of use, and graphical presentation, have been emphasised, but there is no consensus in the literature as to what may be critical to EIS success. The results of a survey of UK executives is used to suggest that the central focus of EIS design and implementation should be on the scanning of corporate external environmental information and the provision of meaningful strategic information.

Over the last three decades, China's agriculture sector has been transformed from the traditional to modern agriculture practice through the effective deployment of Information and Communication Technologies (ICT). Information processing and dissemination have played a critical role in this transformation process. However, there are very limited publications regarding the China's success and lessons learned in utilising ICTs to support Agriculture development and transformation. This paper aims to contribute to a better understanding on how different ICT-based information service models are designed and adopted in China; and to share the knowledge and experience in applying emerging ICTs in disseminating agriculture information to farmers to improve productivity and economic, social and environmental sustainability. The paper reviews and analyses the China's agricultural information service systems and models. Seven ICT-based information dissemination models are identified and discussed. Successful cases are presented to demonstrate the impacts of different service models. The findings provide a useful direction for researchers and practitioners in developing future ICT based information processing and dissemination systems. It is hoped that this paper will also help other developing countries to learn from China's experience and best practice in their endeavor of applying emerging ICTs in agriculture information dissemination and sharing.