DSS (Decision Support Systems) in Indian Organised Retail Sector

Indian organised retail industry is poised for growth. Rapid state of change due to speedy technological developments, changing competitive positions, varying consumer behaviour as well as their expectations and liberalized regulatory environment is being observed in organized retailing. Information is crucial to plan and control profitable retail businesses and it can be an important source of competitive advantage so long as it is affordable and readily available. DSS (Decision Support Systems) which provide timely and accurate information can be viewed as an integrated entity providing management with the tools and information to assist their decision making. The study, exploratory in nature plans to adopt a case study approach to understand practices of organized retailers in grocery sector regarding applications of various DSS tools. Conceptual overview of DSS is undertaken by reviewing the literature. The study attempts to describe practices and usage of DSS in operational decisions in grocery sector and managerial issues in design and implementation of DSS. Comparision across national chain and local organized retailer in grocery sector reveals that national chain having implemented ERP partially are mostly using the same for majority of operational decisions like inventory management, CRM, campaign management. Two local players use spread sheets and in house software to make the above operational decisions. The benefits realized remain the same across the retailers. Prioritization as well as quantification of benefits was not communicated. The issues of coordination, integration with other systems in case of ERP usage, training were highlighted. Future outlook of DSS by the respondents portrayed a promising picture.

Comparison of the Information Technology Development in Slovakia and Hungary

Nowadays the role of information is increasingly important, so every company has to provide the efficient procurement, processing, storage and visualization of this special resource in hope to stay competitive. More and more enterprises introduce Enterprise Resource Planning System to be able to perform the listed functions. The article illustrates the usage of these systems in Hungary and Slovakia, as well as tests the following presumption: the level of Information Technology (IT) development is lower in Hungary than our northern neighbor

A Conceptual Framework for Definition of the Correlation Between Company Size Categories and the Proliferation of Business Information Systems in Hungary Download article

Based on a conceptual model, this paper aims to explore the background of the decision-making process leading to the introduction of business information systems among enterprises in Hungary. Together with presenting the problems arising in the course of the implementation of such systems, their usage patterns are also investigated. A strong correlation is established between the size of an enterprise, the scope of its business activities and the range of the business information systems it applies

Organizational diagnosis in practice : a cross-classification analysis using the DEL-technique

This paper investigates asymmetric effects of monetary policy over the business cycle. A two-state Markov Switching Model is employed to model both recessions and expansions. For the United States and Germany, strong evidence is found that monetary policy is more effective in a recession than during a boom. Also some evidence is found for asymmetry in the United Kingdom and Belgium. In the Netherlands, monetary policy is not very effective in either regime.

Towards Design Principles for Data-Driven Decision Making: An Action Design Research Project in the Maritime Industry

Data-driven decision making (DDD) refers to organizational decision-making practices that emphasize the use of data and statistical analysis instead of relying on human judgment only. Various empirical studies provide evidence for the value of DDD, both on individual decision maker level and the organizational level. Yet, the path from data to value is not always an easy one and various organizational and psychological factors mediate and moderate the translation of data-driven insights into better decisions and, subsequently, effective business actions. The current body of academic literature on DDD lacks prescriptive knowledge on how to successfully employ DDD in complex organizational settings. Against this background, this paper reports on an action design research study aimed at designing and implementing IT artifacts for DDD at one of the largest ship engine manufacturers in the world. Our main contribution is a set of design principles highlighting, besides decision quality, the importance of model comprehensibility, domain knowledge, and actionability of results

Indian Organised Apparel Retail Sector and DSS (Decision Support Systems)

Indian apparel retail sector poses interesting challenges to a manager as it is evolving and closely linked to fashions. Appealing mainly to youth, the sector has typical information requirements to manage its operations. DSS (Decision Support Systems) provide timely and accurate information & it can be viewed as an integrated entity providing management with the tools and information to assist their decision making. The study exploratory in nature, adopts a case study approach to understand practices of organized retailers in apparel sector regarding applications of various DSS tools. Conceptual overview of DSS is undertaken by reviewing the literature. The study describes practices and usage of DSS in operational decisions in apparel sector and managerial issues in design and implementation of DSS. A multi brand local chain and multi brand national chain of apparel was chosen for the study. Varied tools were found to be used by them. It was also found that for sales forecasting and visual merchandising decisions, prior experience rather than any DSS tool was used. The benefits realized were; “help as diagnostic tool”, “accuracy of records and in billing”, “smooth operations”. The implementation issues highlighted by the store managers were; more initial teething problems rather than resistance on the part of employees of the store, need for investment of time & money in training, due to rapid technological advancements, time to time updation in DSS tools is required . Majority of operational decisions like inventory management, CRM, campaign management were handled by ERP (Enterprise Resource Planning) or POS (Point of Sale). Prioritization as well as quantification of benefits was not attempted. The issues of coordination, integration with other systems in case of ERP usage, training were highlighted. Future outlook of DSS seems bright as apparel retailers are keen to invest in technology.

Middle Managers Intention To Use Information In A Data-driven Decision Support System: A Case Study In The Aircraft Industry

As aircraft organizations, like many organizations, seek out ways to increase efficiencies in order to remain competitive within the market, higher utilization of information and personnel become essential. This increase in efficiency will require additional insight into the behavioral intention predictability of middle managers that are responsible for making the decisions that drive efficiencies. Theoretical models such as the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB), and the Technology Acceptance Model (TAM) have linked behavioral intention to predictable behavior. This research study seeks to provide a deeper understanding into the phenomenon of the behavioral intention predictability of middle managers in the aircraft industry to who use information from a data-driven decision support system. The research intends to use a case study methodology utilizing interviews and observations to collect data about attitude, subjective norms, and perceived behavioral controls. All of these play a role in the prediction of behavioral intention. The expectation of the study is to provide organizations, within the aerospace industry, with advanced understanding about behavioral intention predictability to maximize information utilization and performance from a data-driven decision support system. This research study focuses on the measurement of behavioral intention to use, not use itself

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

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

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting 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. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF