Preference Learning in Consecutive Experimental Auctions

This paper explores the origins of the strikingly high price premia paid for new food products in lab valuation exercises. Our experimental design distinguishes between two explanations of this phenomenon: novelty of the experimental experience versus the novelty of the good, i.e., preference learning—bids reflect a person's desire to learn how an unfamiliar good fits into their preference set. Subjects bid in four consecutive experimental auctions for three goods that vary in familiarity, candy bars, mangos, and irradiated meat. Our results suggest that preference learning is the main source of the high premia, and that novelty of the experimental experience does not in itself artificially inflate valuations.     

Exploring justice judgment patterns in Asia: a four country multi-group latent class analysis

We explore workers’ justice judgment patterns to understand how they use information to assess fair treatment at work. Justice judgment patterns are the unique set of information that individuals draw upon and use when evaluating the overall fairness of an entity. Data from four samples of workers from Malaysia, Cambodia, the Philippines, and China were analyzed using a multi-group latent class analysis. Results suggest four classes of justice judgment processes, three of which represent different patterns of heuristic processing. Comprehensive processors use a wide range of information when making justice judgments, while minimalist processors consider a limited range of information. Reward-focused processors focus on distributive justice cues and treatment-focused processors specifically attend to interpersonal justice cues while neglecting distributive justice cues. The latent class structure shared conceptual meaning across countries but the patterns had different rates of representation. Findings suggest that individuals do not always use complete information when assessing how fairly they are treated at work. Many appear to use heuristics that emphasize minimizing information processing, instrumental outcomes, or more relational outcomes. Results and implications are discussed.     

Talking Your Way into Entrepreneurial Support: An Analysis of Satisfaction Drivers in Entrepreneur Mutual Aid Groups

The role of organized peer networks in entrepreneurial support systems has been surprisingly neglected in the literature, despite their undisputed effectiveness in numerous areas outside the entrepreneurship realm. This study explores the efficacy of mutual aid groups for entrepreneurial support, as theoretically distinct from other group‐based mechanisms (such as peer group mentoring and many to one group mentoring). Drawing from respondent data of small, local mutual aid groups within the global entrepreneurship support organization (2,869 responses from members of 540 groups worldwide), we investigate the factors determining the entrepreneurs' satisfaction with the entrepreneur mutual aid groups. Understanding the antecedents of members' subjective satisfaction with the group serves an essential first step toward developing the models explaining the objective effectiveness of these organizations (e.g., performance, survival, and growth), in that the former is an essential, necessary condition for continuing participation in the voluntary mutual aid groups. Our analysis reveals that group climate and leadership are important drivers of group satisfaction.     

Mean-variance optimization using forward-looking return estimates

Despite its theoretical appeal, Markowitz mean-variance portfolio optimization is plagued by practical issues. It is especially difficult to obtain reliable estimates of a stock’s expected return. Recent research has therefore focused on minimum volatility portfolio optimization, which implicitly assumes that expected returns for all assets are equal. We argue that investors are better off using the implied cost of capital based on analysts’ earnings forecasts as a forward-looking return estimate. Correcting for predictable analyst forecast errors, we demonstrate that mean-variance optimized portfolios based on these estimates outperform on both an absolute and a risk-adjusted basis the minimum volatility portfolio as well as naive benchmarks, such as the value-weighted and equally-weighted market portfolio. The results continue to hold when extending the sample to international markets, using different methods for estimating the forward-looking return, including transaction costs, and using different optimization constraints.

     

How (Not) to Foster Innovations in Public Infrastructure Projects*

The government wants an infrastructure‐based public service to be provided. First, the infrastructure has to be built; subsequently, it has to be operated. Should the government bundle the building and operating tasks in a public–private partnership? Or should it choose traditional procurement (i.e., delegate the tasks to different firms)? Each task entails unobservable investments to come up with innovations. It turns out that, depending on the nature of the innovations, bundling can either stimulate or discourage investments. Moreover, we find that if renegotiation cannot be prevented, public–private partnerships might lead the government to deliberately opt for technologically inferior projects.     

Kidnap and ransom insurance: A strategically useful,often undiscussed,marketplace tool for international operations

With kidnaping rates rising, the disruptive forces of kidnaping threaten the stability and success of corporate investment projects and put stress on appropriate corporate governance response methodologies. While kidnaping targets vary considerably among countries where it frequently occurs, most often the goal of kidnapers is money from ransom payments. Financial consequences of a kidnap ransom payment can be severe for companies, and psychological damage can be lasting to employees and their families. Given the increasingly global nature of business and increasing expansion into less politically and legally stable emerging markets, kidnap, ransom, and extortion pose a problem for management of corporations wishing to take advantage of emerging market opportunities. Kidnap and Ransom (K&R) Insurance is a risk control technique used by about 75% of Fortune 500 companies, nongovernmental organizations, and an increasing percentage of small to medium sized companies. It is a bundled package policy that includes the purchase of an insurance policy to indemnify the company for the costs of kidnap, ransom, and extortion. Such policies can also provide protective consulting beforehand, provide crisis response and negotiation assistance, as well as psychological support services after the fact. In this paper, we describe the K&R policy, its history, other nonfinancial corporate benefits provided by K&R policies, and discuss its use by corporate managers for the benefit of corporate, financial, and personnel stability. It can also be used in course on managing international risk.     

‘Howzat’—how do artefacts without matter,matter? The case of decision review systems in professional cricket

It has been argued that the social and material worlds are increasingly entangled as they become mediated by and experienced through virtual representations of live events. Virtual decision review systems in professional sport provide an albeit unusual case study example of such developments where virtual (re‐)representations of events are increasingly used in match play to inform adjudicator decisions concerning ‘what really happened’. This has prompted an ongoing debate in many sports over both the accuracy and appropriateness of these technologies for representing events which are often fast moving and difficult to judge with the human eye. We explore these issues using a sociomaterial practice lens and indicate the broader relevance of the case for basing judgements and decisions on virtual views of reality.