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1 – 10 of 22Wayne S. DeSarbo, Rajdeep Grewal, Heungsun Hwang and Qiong Wang
The purpose of this paper is to integrate aspects of the literature on strategic and performance groups and explicitly derive strategic/performance groups which exhibit…
Abstract
Purpose
The purpose of this paper is to integrate aspects of the literature on strategic and performance groups and explicitly derive strategic/performance groups which exhibit differences with respect to both strategy and performance, as well as display associations and potential interrelationships between the two sets of variables.
Design/methodology/approach
A two‐way clusterwise bilinear spatial model was formulated (e.g. a scalar products or vector multidimensional scaling model (MDS)) for the analysis of two‐way strategic and performance data which simultaneously performs MDS and cluster analysis. An efficient alternating least‐squares procedure was devised that estimates conditionally globally optimum estimates of the model parameters within each iterate in analytic, closed‐form expressions.
Findings
This bilinear MDS methodology was deployed in the context of strategic/performance group estimation using archival data for public banks in the NY‐NJ‐PA tri‐state area. For this illustration, four strategic/performance groups and two underlying dimensions were found.
Practical implications
Consideration of both strategy and performance data should be employed in describing the heterogeneity amongst firms competing in the same industry.
Originality/value
The paper provides a new spatial methodology to derive strategic/performance groups in any given industry to more completely summarize intra‐industry heterogeneity.
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Joanne Jin Zhang, Yossi Lichtenstein and Jonathan Gander
Digital business models are often designed for rapid growth, and some relatively young companies have indeed achieved global scale. However, despite the visibility and importance…
Abstract
Digital business models are often designed for rapid growth, and some relatively young companies have indeed achieved global scale. However, despite the visibility and importance of this phenomenon, analysis of scale and scalability remains underdeveloped in management literature. When it is addressed, analysis of this phenomenon is often over-influenced by arguments about economies of scale in production and distribution. To redress this omission, this paper draws on economic, organization, and technology management literature to provide a detailed examination of the sources of scaling in digital businesses. We propose three mechanisms by which digital business models attempt to gain scale: engaging both non-paying users and paying customers; organizing customer engagement to allow self-customization; and orchestrating networked value chains, such as platforms or multi-sided business models. Scaling conditions are discussed, and propositions developed and illustrated with examples of big data entrepreneurial firms.
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Mahima Hada, Rajdeep Grewal and Gary L. Lilien
From the supplier firm's perspective, a referral is a recommendation from A (the referrer) to B (the potential customer) that B should, or should not, purchase from C (the…
Abstract
From the supplier firm's perspective, a referral is a recommendation from A (the referrer) to B (the potential customer) that B should, or should not, purchase from C (the supplier firm). Thus, as referrals are for a specific supplier firm, they should be viewed as part of the supplier firm's marketing and sales activities. We recognize three types of referrals – customer-to-potential customer referrals, horizontal referrals, and supplier-initiated referrals – that have critical roles in a potential customer's purchase decision. We develop the concept of referral equity to capture the net effect of all referrals for a supplier firm in the market. We argue that supplier firms should view referral equity as a resource that has financial value to the firm as it affects the firm's cash flows and profits. We offer strategies firms can use to manage referrals and build their referral equity and suggest a research agenda.