Jan Ketil Arnulf

Trust and knowledge creation: how the dynamics of trust and absorptive capacity may affect supply chain management development projects

A case study is presented from a project where five companies representing manufacturer, wholesaler and retailer roles tried to establish supply chain management practices. The researchers had the role of project managers and facilitators, thereby acting as action researchers. Although devised and conducted in a way that seemed adequate to the participants, the project was only partly successful. Our analysis of the case shows that dynamics of institutional trust and distrust caused obstructions to the mutual learning capacities of the participating companies. If the project management had been able to attend to and manage these dynamics in a more reflective manner, the project may have been more successful. This hypothesis is substantiated through quantitative analysis of accountancy data from one participating company as well as qualitative analysis of transcripts from project meetings.

Predicting Survey Responses: How and Why Semantics Shape Survey Statistics on Organizational Behaviour

Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60–86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.

Impression making by résumé layout: Its impact on the probability of being shortlisted

This study examines the effect of the graphical layout of résumés on the shortlisting of applicants for employment interviews. Previous research has investigated the effect of bad printing quality, but this research has explored the impact of a creative layout of résumés of equal quality. A sample of 90 respondents (half professional recruiters, half students) was asked to rank 12 candidates applying for one vacancy. All 12 candidates were presented an equal number of times in three different layout formats—formal on white paper, coloured, and “creative” design. Results suggest that the graphical design may have a substantial impact on the likelihood of being shortlisted, where formal designs were preferred over the “creative” layouts. Professional recruiters were only slightly less influenced by the layout than nonprofessionals. Implications for employers and jobseekers are discussed.

Respondent Robotics: Simulating Responses to Likert-Scale Survey Items

The semantic theory of survey responses (STSR) proposes that the prime source of statistical covariance in survey data is the degree of semantic similarity (overlap of meaning) among the items of the survey. Because semantic structures are possible to estimate using digital text algorithms, it is possible to predict the response structures of Likert-type scales a priori. The present study applies STSR in an experimental way by computing real survey responses using such semantic information. A sample of 153 randomly chosen respondents to the Multifactor Leadership Questionnaire (MLQ) was used as target. We developed an algorithm based on unfolding theory, where data from digital text analysis of the survey items served as input. Upon deleting progressive numbers (from 20%-95%) of the real responses, we let the algorithm replace these with simulated ones, and then compared the simulated datasets with the real ones. The simulated scores displayed sum score levels, alphas, and factor structures highly resembling their real origins even if up to 86% were simulated. In contrast, this was not the case when the same algorithm was operating without access to semantic information. The procedure was briefly repeated on a different measurement instrument and a different sample. This not only yielded similar results but also pointed to need for further theoretical and practical developments. Our study opens for experimental research on the effect of semantics on survey responses using computational procedures.

How FIEs may sustain competitive advantage in China Adapting marketing strategy by the use of Guanxi

Purpose – The purpose of this paper is to show that the Guanxi characteristics in Chinese business culture may add to the understanding of foreign invested enterprises (FIE) successful marketing in China. Design/methodology/approach – The authors surveyed the entry mode of 296 FIEs in China and examined their way of adapting marketing strategy to local culture. The authors used a conceptual model hypothesizing a system of variables that the authors subsequently tested using structural equation modeling. Findings – Market orientation was insufficient to obtain marketing capability in China. FIE marketing capability in China was dependent on Guanxi and learning orientation, showing the need for contextualization of marketing approaches. Research limitations/implications – This paper enriches previous research on marketing and makes a contribution to the existing literature on practical management in China. It is also relevant for marketing in other markets in transition. Practical implications – FIEs may d...

The failing measurement of attitudes: How semantic determinants of individual survey responses come to replace measures of attitude strength

The traditional understanding of data from Likert scales is that the quantifications involved result from measures of attitude strength. Applying a recently proposed semantic theory of survey response, we claim that survey responses tap two different sources: a mixture of attitudes plus the semantic structure of the survey. Exploring the degree to which individual responses are influenced by semantics, we hypothesized that in many cases, information about attitude strength is actually filtered out as noise in the commonly used correlation matrix. We developed a procedure to separate the semantic influence from attitude strength in individual response patterns, and compared these results to, respectively, the observed sample correlation matrices and the semantic similarity structures arising from text analysis algorithms. This was done with four datasets, comprising a total of 7,787 subjects and 27,461,502 observed item pair responses. As we argued, attitude strength seemed to account for much information about the individual respondents. However, this information did not seem to carry over into the observed sample correlation matrices, which instead converged around the semantic structures offered by the survey items. This is potentially disturbing for the traditional understanding of what survey data represent. We argue that this approach contributes to a better understanding of the cognitive processes involved in survey responses. In turn, this could help us make better use of the data that such methods provide.

Predicting the immediate future: An intervention to stimulate reflection in management groups

Abstract The purpose of the present study was to test ways of stimulating the reflective capacity in 10 regional management groups in a nation-wide Scandinavian wholesales company. Two types of intervention based on converging theoretical arguments were devised. The first intervention had the management groups predict key financial figures every month. A second intervention was introduced by the top management team itself, differing in form, but based on the experience from the first. The co-variation with organizational performance and an exploration of the possible mechanisms implied were analysed over a time-line spanning five budgetary years. Analyses indicate that the interventions were contributing to the intended changes. The possible mechanisms are discussed in connection to accountability, goal setting and reflection.