DESIGN AND DELIVERY OF ELECTRONIC SERVICES: IMPLICATIONS FOR CUSTOMER VALUE IN ELECTRONIC FOOD RETAILING

Electronic food retailers can satisfy their customers more effectively if they understand how this particular market works. As in other service segments, the emergence of electronic business-to-customer services in the retail food industry poses questions for managers about the design of new food retailing services and the redesign of existing services for delivery through electronic channels. Important topics include characteristics of electronic service offerings, the typical operational configurations used to deliver electronic services, and the ways in which they relate to the effectiveness of electronic service delivery. We address this issue by developing a product-process matrix for understanding and analyzing electronic retailing services in general. We tailor the matrix to food retailing in particular. The product-process matrix allows electronic food retailers to determine in advance what features they need in a web site to serve their chosen market effectively.Consumer/Household Economics, Marketing, Research and Development/Tech Change/Emerging Technologies,

Business intelligence as the support of decision-making processes in e-commerce systems environment

The present state of world economy urges managers to look for new methods, which can help to start the economic growth. To achieve this goal, managers use standard as well as new procedures. The fundamental prerequisite of the efficient decision-making processes are actual and right information. Managers need to monitor past information and current actual information to generate trends of future development based on it. Managers always should define strictly what do they want to know, how do they want to see it and for what purpose do they want to use it. Only in this case they can get right information applicable to efficient decision-making. Generally, managers´ decisions should lead to make the customers´ decision-making process easier. More frequently than ever, companies use e-commerce systems for the support of their business activities. In connection with the present state and future development, cross-border online shopping growth can be expected. To support this, companies will need much better systems providing the managers adequate and sufficient information. This type of information, which is usually multidimensional, can be provided by the Business Intelligence (BI) technologies. Besides special BI systems, some of BI technologies are obtained in quite a few of ERP (Enterprise Resource Planning) systems. One of the crucial questions is whether should companies and firms buy or develop special BI software, or whether they can use BI tools contained in some ERP systems. In respect of this, there is a question if the modern ERP systems can provide the managers sufficient possibilities relating to ad-hoc reporting, static and dynamic reports and OLAP analyses. A one of the main goals of this article is to show and verify Business Intelligence tools of Microsoft Dynamics NAV for the support of decision-making in terms of the cross-border online purchasing. Pursuant to above-mentioned, in this article authors deal with problems relating to managers´ decision-making, customers´ decision-making and a support of its using the BI tools contained in ERP system Microsoft Dynamics NAV. A great deal of this article is aimed at area of multidimensional data which are the source data of e-commerce systems.Business Intelligence, decision-making, e-commerce system, cross-border online purchasing, multi-dimensional data, reporting, data visualization

Recent advances in industrial wireless sensor networks towards efficient management in IoT

With the accelerated development of Internet-of- Things (IoT), wireless sensor networks (WSN) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for wireless sensor networks design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross layer design of lightweight and cloud-based RESTful web service

Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Marketing relations and communication infrastructure development in the banking sector based on big data mining

Purpose: The article aims to study the methodological tools for applying the technologies of intellectual analysis of big data in the modern digital space, the further implementation of which can become the basis for the marketing relations concept implementation in the banking sector of the Russian Federation‘ economy. Structure/Methodology/Approach: For the marketing relations development in the banking sector in the digital economy, it seems necessary: firstly, to identify the opportunities and advantages of the big data mining in banking marketing; secondly, to identify the sources and methods of processing big data; thirdly, to study the examples of the big data mining successful use by Russian banks and to formulate the recommendations on the big data technologies implementation in the digital marketing banking strategy. Findings: The authors‘ analysis showed that big data technologies processing of open online and offline sources of information significantly increases the data amount available for intelligent analysis, as a result of which the interaction between the bank and the target client reaches a new level of partnership. Practical Implications: Conclusions and generalizations of the study can be applied in the practice of managing financial institutions. The results of the study can be used by bank management to form a digital marketing strategy for long-term communication. Originality/Value: The main contribution of this study is that the authors have identified the main directions of using big data in relationship marketing to generate additional profit, as well as the possibility of intellectual analysis of the client base, aimed at expanding the market share and retaining customers in the banking sector of the economy.peer-reviewe

Local Economic Development Policies

This chapter seeks to provide useful advice for local government policy towards economic development programs. The chapter: reviews the size and scope of local economic development programs in the United States; critically analyzes the various rationales offered for these programs; makes recommendations for what local policy should do about business attraction and incentives, business retention, new business development, high technology development, brownfield development, distressed neighborhoods, and downtowns; and discusses how local economic development programs should be organized, managed, and evaluated.local, regional, economic, development, Bartik, Upjohn

B2C Mass Customization in the Classroom

The purpose of this article is to describe an internet-based mass customization assignment in Operations Management/Supply Chain Management classes where students utilize the Web site of a company that offers a customized product. Students evaluate the user interface, judge the value proposition of the product they demonstrate, and discuss issues of product design, process design and scheduling, inventory management, Supply Chain Management, marketing, and competitors. The students learn about mass customization from both the producer\u27s perspective and the consumer\u27s perspective. Through their own research and the class presentations students are able to develop a better understanding of the implementation requirements and challenges of mass customization. The assignment is highly interactive and has been successfully used in Operations Management and Supply Chain Management courses at under-graduate and graduate levels and at multiple universities. In addition, practitioners interested in implementing a mass customization process can use the assignment as a brainstorming or benchmarking exercise