Understanding the factors affecting e-business adoption and impact on logistics processes

Purpose: The purpose of this paper is to conceptualize e-business adoption and to generate understanding of the range of factors affecting the adoption process. The paper also aims at exploring the perceived impact of e-business adoption on logistics-related processes. Design/methodology/approach: Case study research, by conducting in-depth interviews in eight companies. Findings: E-business adoption is not exclusively a matter of resources. Increased e-business adoption and impact are caused by increased operational compatibility, as well as increased levels of collaboration. In terms of e-business impact this mainly refers to cycle time reductions and quality improvements, rather than direct cost reductions as reported by other authors. Research limitations/implications: The intrinsic weakness of the research method and the way concepts are operationalized limits the ability to generalize findings. Practical implications: Managers should emphasize developing their relationships with theirsuppliers/customers, in an effort to do common e-business investments, and should aim to increase their partners' commitment to the use of these applications. Originality/value: This paper provides empirical evidence from a sector where limited research efforts have taken place. Explanations can be helpful to other researchers involved in the understanding of the adoption of e-business and its impact. © Emerald Group Publishing Limited.

RFID adoption issues in the warehouse

In recent years the increased interest in introducing radio frequency technology (RFID) in warehousing was observed. First adopters of RFID reported numerous benefits, which included: reduced shrinkage, real-time tracking and better accuracy of data collection. Along with the academic and industrial discussion on benefits which can be achieved in RFID enabled warehouses there are reports on issues related to adoption of RFID technology in warehousing. This paper reviews results of scientific reports of RFID implementation in warehouses and discusses the adoption barriers and causes of not achieving full potential of the technology. Following adoption barriers are identified and set in warehousing context: lack of forseeable return on investment (ROI), unreliable performance of RFID systems, standarisation, integration with legacy systems and privacy/security concerns. As more studies will address these challenges, the realisation of RFID benefits for warehouses will become reality.

The right time and place:strategic positioning for competitive manufacture

Increasingly in the UK, companies that have traditionally considered themselves as manufacturers are being advised to now see themselves as service providers and to reconsider whether to have any production capability. A key challenge is to translate this strategy into a selection of product and service-centred activities within the company's supply chain networks. Strategic positioning is concerned with the choice of business activities a company carries out itself, compared to those provided by suppliers, partners, distributors and even customers. In practice, strategic positioning is directly impacted by such decisions as outsourcing, off-shoring, partnering, technology innovation, acquisition and exploitation. If companies can better understand their strategic positioning, they can make more informed decisions about the adoption of alternative manufacturing and supply chain activities. Similarly, they are more likely to reject those that, like off-shoring, are currently en vogue but are highly likely to erode competitive edge and business success. Our research has developed a new concept we call 'competitive space' as a means of appreciating the strategic positioning of companies, along with a structured decision process for managing competitive space. Our ideas about competitive space, along with the decision process itself, have been developed and tested on a range of manufacturers. As more and more manufacturers are encouraged to move towards system integration and a serviceable business model, the challenge is to identify the appropriate strategic position for their organisations, or in other words, to identify their optimum competitive space for manufacture.

Enhanced renewable energy adoption for sustainable development in India:interpretive structural modeling approach

Poverty alleviation and social upliftment of rural India is closely linked with the availability and use of energy for development. At the same time, sustainable supply of clean and affordable renewable energy sources is required if development is to be sustainable, so that it does not cause any environmental problems. The purpose of this paper is to determine the key variables of renewable energy implementation for sustainable development, on which the top management should focus. In this paper, an interpretive structural modeling (ISM) - based approach has been employed to model the implementation variables of renewable energy for sustainable development. These variables have been categorized under ‘enablers’ that help to increase the implementation of renewable energy for sustainable development. A major finding of this research is that public awareness regarding renewable energy for sustainable development is a very significant enabler. In this paper, an interpretation of variables of renewable energy for sustainable development in terms of their driving and dependence powers has been examined. For better results, top management should focus on improving the high-driving power enablers such as leadership, strategic planning, public awareness, top management support, availability of finance, government support, and support from interest groups.

Exploring the impact of e-business adoption on logistics processes:empirical evidence from the food industry

The objectives of the research were to identify factors that influence e-business adoption and its impact on logistics processes in the Greek food industry. Drawing on existing research, a conceptual framework and propositions were developed and six in depth case studies were carried out. In the framework, three major categories of influencing factors were distinguished: intra-enterprise, sector and supply chain factors. Findings suggest that e-business adoption is more affected by supply chain and sector factors, rather than intra-enterprise factors. Regarding the impact of e-business on logistics process, it seems that it is affected by the frequency of its use and it is greater in processes occurring at the company-customer interface. Finally, e-business impact is more related to the dimensions of time and quality, rather than cost improvements.

ICT adoption by logistics service providers:developing a learning agenda

Recent years have seen innovations in the logistics and freight transport industry in relation to Information and communication technologies (ICT) diffusion. The implementation of such technologies by third party logistics providers (3PLs) allows the real-time exchange of information between supply chain partners, thereby improving planning capability and customer service. However, the logistics and freight transport industry is lagging somewhat behind other sectors in ICT diffusion. In relation to the latter point, it is important to note that the dissemination of ICT in logistics and supply chain management (SCM) is shifting the 3PL industry to an increasingly knowledge-intensive approach. In this process, the role of learning becomes more central and an assessment of the impact of future ICT learning needs for the logistics providers is a strategic imperative. The aim of this paper is to assess the impact of ICT on logistics and freight transport industry in Italy and Ireland, and to identify learning needs for more effective ICT adoption in 3PLs.

"We don't need no education" - Or do we? Management education and alumni adoption of strategy tools

Despite concerns about the relevance of management education, there is relatively little evidence about whether graduates use the management tools and concepts they are taught. We address this gap with evidence from a survey of business school alumni adoption of tools typically taught in strategic management courses. Our findings show that four educational characteristics-level of formal education, frequency of management training, specificity of strategic management education, and time elapsed since formal education-drive adoption of strategy tools. Specifically, features such as postgraduate over undergraduate qualifications and frequent exposure to management training predispose greater user of strategy tools. However, other factors, such as time elapsed since formal education, are not as great a predictor of variation in use. We conclude with a predictive model of the relative weight and importance of educational and demographic characteristics on strategy tool adoption and discuss our findings in light of the relevance debate. © The Author(s) 2013.

Ontology forecasting in scientific literature:semantic concepts prediction based on innovation-adoption priors

The ontology engineering research community has focused for many years on supporting the creation, development and evolution of ontologies. Ontology forecasting, which aims at predicting semantic changes in an ontology, represents instead a new challenge. In this paper, we want to give a contribution to this novel endeavour by focusing on the task of forecasting semantic concepts in the research domain. Indeed, ontologies representing scientific disciplines contain only research topics that are already popular enough to be selected by human experts or automatic algorithms. They are thus unfit to support tasks which require the ability of describing and exploring the forefront of research, such as trend detection and horizon scanning. We address this issue by introducing the Semantic Innovation Forecast (SIF) model, which predicts new concepts of an ontology at time t + 1, using only data available at time t. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed approach offers a competitive boost in mean average precision-at-ten compared to the baselines when forecasting over 5 years.