Alan A. Brandyberry

Determinants of adoption for organisational innovations approaching saturation

A large‐scale random sample is used to empirically examine the relationships between adoption of computer‐aided design (CAD) and five organisational characteristics that are likely to affect the probability of a firm adopting an information technology. The organisational characteristics tested are bureaucratic control, internal communication, external communication, organisational innovation, and the firm’s size. Results indicate that bureaucratic control, internal communication, and external communication do affect the likelihood of a firm adopting CAD but organisational innovation and organisational size do not. These results suggest there are differences and similarities between the organisational influences associated with classic adoption models developed with emerging technologies and the organisational influences associated with CAD adoption and possibly other mature information technologies.

Organizational Slack and Information Technology Innovation Adoption in SMEs

This study explores the relevant dimensions of organizational slack in small and medium enterprises (SMEs) and investigates their impact on adoption of different types of information technology (IT) innovations. Using recent data from a representative sample of 2,296 U.S. SMEs, we find that the slack-innovation relationships previously described in larger firms do not hold well for SMEs. Our results show potential slack (measured as access to external credit) to be a strong predictor of technology adoption in SMEs. By contrast, available slack appeared not to be a significant factor in SME innovation adoption. Moreover, the direction of the effects of potential slack was moderated by the capital-intensity of the innovation. In particular, e-commerce, which required lesser financial resources for SME adoption, was found to be pursued by those with lesser potential slack. We argue that, in some cases, innovation adoption may represent a form of “bricolage†by resource constrained SMEs.

Measuring Arbitrage Opportunities: A Minimum Performance Inefficiency Estimation Technique

Entrepreneurs respond to opportunities that come in two basic forms: innovation and arbitrage. This article presents a technique called the minimum performance inefficiency (MPI) estimation method that could be used to estimate arbitrage opportunities. The technique has several advantages over the conceptually similar data envelopment analysis (DEA) and other techniques. The authors validate the technique with a well-known data set and illustrate its use based on secondary data from the publishing industry.

The e-tailer's dilemma

The e-tailers dilemma refers to the difficulty web-based retailers (or e-tailers) have experienced in achieving profitability. The problem centers on the need to increase effective (purchasing) visitors and on the increased costs associated with the electronic commerce infrastructure upgrades necessary to service these additional visitors. This may lead e-tailers into a cycle of achieving increased revenues that are merely offset by rising costs. There are ample examples where commonly employed metrics (unique visitors, page views, sales, etc.) suggest success while companies struggle to obtain profitability. This paper examines several aspects of this dilemma. The formalization of both the tangible and intangible aspects of an electronic commerce infrastructure is proposed. Next, an intuitive, utility-based model to help describe and interpret e-tail visitor dynamics is developed. Finally, a visitor function model of e-tail profitability incorporating necessary infrastructure improvements and visitor characteristics is developed.

Maximally productive input-output units

Abstract Technical or Pareto–Koopmans efficiency models can be based on ratios of weighted sums of outputs to weighted sums of inputs. Differing meanings have been considered for such factor weights. In this paper, we use value or cost rate meanings depending on model orientation. These meanings permit considering the simultaneous assignment of input and output factor weights along with optimal intensity values for a virtual composite unit constructed from the observed units. An optimization principle we call the winners-take-all criterion is proposed for determining the maximally productive unit(s). No assumptions are required on the internal transformation processes of the units. The model simultaneously determines the intensities and factor weights and results in indefinite quadratic programming problems that simplify to linear programming in certain cases. For the general case, genetic search is applied. Numerical illustrations are provided for faculty merit scoring and for the 15 hospital dataset of Sherman.

Linear programming system identification

We define a version of the Inverse Linear Programming problem that we call Linear Programming System Identification. This version of the problem seeks to identify both the objective function coefficient vector and the constraint matrix of a linear programming problem that best fits a set of observed vector pairs. One vector is that of actual decisions that we call outputs. These are regarded as approximations of optimal decision vectors. The other vector consists of the inputs or resources actually used to produce the corresponding outputs. We propose an algorithm for approximating the maximum likelihood solution. The major limitation of the method is the computation of exact volumes of convex polytopes. A numerical illustration is given for simulated data.

Linear programming system identification: The general nonnegative parameters case

Abstract By linear programming system identification, we mean the problem of estimating the objective function coefficient vector π and the technological coefficient matrix A for a linear programming system that best explains a set of input–output vectors. Input vectors are regarded as available resources. Output vectors are compared to imputed optimal ones by a decisional efficiency measure and a likelihood function is constructed. In an earlier paper, we obtained results for a simplified version of the problem. In this paper, we propose a genetic algorithm approach for the general case in which π and A are of arbitrary finite dimensions and have nonnegative components. A method based on Householder transformations and Monte Carlo integration is used as an alternative to combinatorial algorithms for the extreme points and volumes of certain required convex polyhedral sets. The method exhibits excellent face validity for a published test data set in data envelopment analysis.

How Experience and Expertise Affect the Use of a Complex Technology

As end-users work with increasingly complex technologies, it is important that these technologies be used to the fullest extent possible. Time is needed to learn how to use these new technologies and fit them to user tasks, but the fact that a user has gained experience does not mean that expertise has also been gained. Using survey data collected from 187 data warehouse end-users, we found that experience and expertise have a significant positive correlation (r = 0.35, p < 0.001), but expertise has a significantly greater effect on ease-of-use perceptions (t=10.2, p < 0.0001) and the use of a technology (t=21.08, p < 0.0001) than experience. Therefore, it is critical that researchers properly delineate which construct – end-user expertise or experience – is being assessed, when measuring the effect that individual differences have on the perceptions and use of technology.

An RBV and real options-based soft OR heuristic for solution strategising

This paper develops a heuristic for applying the abstract and complex theories of real options and the resource-based view (RBV) to provide managerial prescription on promising technology solutions to business problems. We draw upon the tradition of soft operational research (OR) with its reliance on graphical techniques to develop a decision-making matrix called the CUReO Grid for identifying preferred solutions under different conditions of decision context uncertainty and the capability of the firm to exploit the technologies under consideration. Our grid is obtained by a two-stage mapping of the real options available in a technology solution, such as options for altering scale and scope or for strategic growth, to a two-dimensional space defined by contextual uncertainty and firm capability. We illustrate our general methodology by applying it to two very different but major contemporary problems: enterprise integration in information technology and lean production in operations management.

A Study of the Effects of Social Factors and Innovation Characteristics on Search Effort and Uncertainty in Mobile App Adoption

The mobile economy is growing rapidly and creating increasingly diversified digital products available to consumers. Due to the cognitive limitation of adopters, they often face the issue of information overload. In order to cope with such issues, adopters typically utilize other information to reduce their uncertainty before adoption. This study focuses on determinants of uncertainty reduction during the adoption process. We do not study why individuals adopt mobile apps, but rather we are studying what perceptions individuals have on the innovation characteristics and social factors (such as friends who use and like the app) and how those perceptions affect their level of search effort and uncertainty. Innovation diffusion theory, herding behavior theory, information overload theory, and the theory of informational cascades are employed in the development of our research model. Findings from this study provide significant insights for developers and management in the mobile app economy.