Agility of the firm : customer's perspective

Agility is emerging as an important determinant of success and achieving sustained competitive advantage in hyper-competition. Whilst the digital natives are on the rise, ubiquitous technologies, networks and associated systems are increasingly weaving themselves into the very fabric of everyday life of both individuals and corporations. With a global shift towards “everywhere retailing”, ubiquitous contemporary information systems such as mobile CRM systems (C-CRMS) are evolving. Unlike in traditional CRMS, customers are becoming an important user group in this new paradigm. Draws on agility literature, this study examine how customers’ use of C-CRMS influence firm’s customer sensing capability, firm’s customer responding capability, and how customer-perceived firm’s responsiveness influence customers use of C-CRMS. Following the notions of agility we theorized firm’s customer agility from customers’ standpoint where we use customers’ use of C-CRMS and customer-perceived firm’s responsiveness for sensing and responding components of agility respectively. This research-in-progress paper investigates how C-CRMS facilitates firm’s customer agility, and reports the approach pursued in adopting sense and response measures of customer agility taking the customers perspective derived through extant literature.

Provision of customer knowledge to supply chains

Knowledge about customers is vital for supply chains in order to ensure customer satisfaction. In an ideal supply chain environment, supply chain partners are able to perform planning tasks collaboratively, because they share information. However, customers are not always able or willing to share information with their suppliers. End consumers, on the one hand, do not usually provide a retail company with demand information. On the other hand, industrial customers might consciously hide information. Wherever a supply chain is not provided with demand forecast information, it needs to derive these demand forecasts by other means. Customer Relationship Management provides a set of tools to overcome informational uncertainty. We show how CRM and SCM information can be integrated on the conceptual as well as technical levels in order to provide supply chain managers with relevant information.

Agility : customer's perspective

In competitive environments agility is emerging as an important determinant of success. Despite the widely accepted importance of agility there has been paucity in research on this construct, especially the customer’s perspective of agility. Rise of digital natives together with growth of ubiquitous information systems has changed the way firms engage with their customers. Firms are finding it difficult to establish sustained loyalty hence the long term sustained advantage over competition. Hence, firms are increasingly investing substantial resources on dynamic Customer Relationship Management systems such as mobile-CRMS to better engage with customers to sense and respond quickly (Agility of the firm) to their demands. This paper investigates firm’s customer agility from customer’s perspective, and we propose a model to understand firm’s customer agility from customer’s point of view. The proposed model is derived based on previous conceptions of agility and the expectation confirmation theory (ECT). This paper reports the initial findings of this study obtained through a pilot test. The findings of the study demonstrate that customer’s view point on firm’s customer agility is an important determinant of achieving success through sustained competitive advantage.

An interpretive field study of packaged software selection processes

Packaged software is pre-built with the intention of licensing it to users in domestic settings and work organisations. This thesis focuses upon the work organisation where packaged software has been characterised as one of the latest ‘solutions’ to the problems of information systems. The study investigates the packaged software selection process that has, to date, been largely viewed as objective and rational. In contrast, this interpretive study is based on a 21⁄2 year long field study of organisational experiences with packaged software selection at T.Co, a consultancy organisation based in the United Kingdom. Emerging from the iterative process of case study and action research is an alternative theory of packaged software selection. The research argues that packaged software selection is far from the rationalistic and linear process that previous studies suggest. Instead, the study finds that aspects of the traditional process of selection incorporating the activities of gathering requirements, evaluation and selection based on ‘best fit’ may or may not take place. Furthermore, even where these aspects occur they may not have equal weight or impact upon implementation and usage as may be expected. This is due to the influence of those multiple realities which originate from the organisational and market environments within which packages are created, selected and used, the lack of homogeneity in organisational contexts and the variously interpreted characteristics of the package in question.

A business engineering approach to client relationship management in a knowledge based firm

This thesis examines Customer Relationship Management and how the capabilities of an organisation to innovate can be enhanced via its implementation in a Knowledge Based Firm. The research identifies current customer knowledge components within an organisation and identifies for future use, CRM components for implementation within a Knowledge Based Firm. Opinions from a panel of experts' are identified for best practice customer relationship strategy, the most important CRM processes and identification of customer knowledge components that will form the basis of implementing a successful CRM to gain a competitive advantage through enhancing the innovative capability for a Knowledge Based Firm.

Agility in consumer retail: sense-response alignment through the eyes of customers

In hyper competition, firms that are agile: sensing and responding better to customer requirements tend to be more successful and achieve supernormal profits. In spite of the widely accepted importance of customer agility, research is limited on this construct. The limited research also has predominantly focussed on the firm’s perspective of agility. However, we propose that the customers are better positioned to determine how well a firm is responding to their requirements (aka a firm’s customer agility). Taking the customers’ stand point, we address the issue of sense and respond alignment in two perspectives-matching and mediating. Based on data collected from customers in a field study, we tested hypothesis pertaining to the two methods of alignment using polynomial regression and response surface methodology. The results provide a good explanation for the role of both forms of alignment on customer satisfaction. Implication for research and practice are discussed.

Decision-theoretic designs for dose-finding clinical trials with multiple outcomes

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.