Re‐storying the Business,Innovation and Entrepreneurial Ecosystem Concepts: The Model‐Narrative Review Method

We propose a novel literature review method in order to systematically trace and reveal the dominant narratives of a body of literature: the model‐narrative review method. We apply this method to an ever‐growing literature on ecosystems in business studies, as it resembles a rich knowledge base with somewhat competing, overarching stories, replete with emplotted characters, systematic puzzles and embellished scientific drama. To interpret these unfolding storylines, we both separately engage with and connect seminal work on business, entrepreneurial and innovation ecosystems. Through thematic reading we map the key themes and scientific puzzles in each ecosystem type. Through enstoried reading we identify how authors construct the plot, narrative setting, emplotted characters, narrative voices and moral lessons around ecosystems. Through rhetorical reading we explicate the rhetorical devices and strategies that claim the relevance of their work. Our findings expose a number of hidden meanings and underlying assumptions, adding transparency to ecosystem rhetorics and enhancing conceptual clarity. Altogether, this method offers a systematic construction of model‐narratives to synthesize and critically reflect upon similarities and differences between related concepts and opens up space for alternative research questions.     

An Analysis of Dual‐Kanban Just‐In‐Time Systems in a Non‐Repetitive Environment

Recent advances in approaches and production technologies for the production of goods and services have made just‐in‐time (JIT) a strong alternative for use in intermittent and small batch production systems, especially when time‐based competition is the norm and a low inventory is a must. However, the conventional JIT system is designed for mass production with a stable master production schedule. This paper suggests supplementing the information provided by production kanbans with information about customer waiting lines to be used by operators to schedule production in each work‐station of intermittent and small batch production systems. This paper uses simulation to analyze the effect of four scheduling policy variables—number of kanbans, length of the withdrawal cycle, information about customer waiting lines, and priority rules on two performance measures—customer wait‐time and inventory. The results show that using information about customer waiting lines reduces customer wait‐time by about 30% while also reducing inventory by about 2%. In addition, the effect of information about customer waiting lines overshadows the effect of priority rules on customer wait‐time and inventory.     

‘Full‐time is a Given Here’: Part‐time Versus Full‐time Job Quality*

This study explores full‐time workers' understanding of and assumptions about part‐time work against six job quality components identified in recent literature. Forty interviews were conducted with employees in a public sector agency in Australia, a study context where part‐time work is ostensibly ‘good quality’ and is typically long term, voluntary, involving secure contracts (i.e. permanent rather than casual) and having predictable hours distributed evenly over the week and year. Despite strong collective bargaining arrangements as well as substantial legal and industrial obligations, the findings revealed some serious concerns for part‐time job quality. These concerns included reduced responsibilities and lesser access to high status roles and projects, a lack of access to promotion opportunities, increased work intensity and poor workplace support. The highly gendered, part‐time labour market also means that it is women who disproportionately experience this disadvantage. To foster equity, greater attention needs to focus on monitoring and enhancing job quality, regardless of hours worked.     

Investigating Unpaid Overtime Working among the Part‐time Workforce

This paper considers whether unpaid overtime working relates to contracted working hours (i.e. whether an employee works part‐time or full‐time) in Britain. It uses the authoritative 2004 British data set Workplace Employment Relations Survey to derive a sample of 4,530 workers, from 735 workplace establishments, who worked unpaid overtime. It tests hypotheses linking contracted working hours to unpaid overtime, and whether this link is moderated by gender, occupational group and the availability of flexible working arrangements. Part‐time workers were found to work significantly more unpaid overtime hours compared with their full‐time counterparts. Gender, occupation and flexible working practices moderated this relationship, where the extent to which part‐timers work more unpaid overtime than their full‐time counterparts was greater for men than for women, was greater for professional/managerial part‐time workers compared with other occupations, and was more evident in establishments less likely to offer flexible working arrangements. The findings raise concerns about the exploitation of part‐time workers.     

Religious Social Identities in the Hybrid Self‐presentations of Sikh Businesspeople

This paper explores the identity work practices of Thai Sikh businesspeople. The paper focuses on two important social identities in participants’ self‐presentations – those derived from religious (Sikh) and western business discourses – and identifies powerful tensions in their hybrid identity work. Conducting discourse analysis on identity work practices within interview settings, the authors explore how participants resolve, accommodate or reject these discursive tensions while attempting stable and coherent hybrid self‐presentations. They identify several different forms of hybridity, including what they term ‘equipollence’, which occurs when two equally powerful, contradictory discourses are incorporated in self‐presentations, producing potentially irresolvable intersections and leading to a lack of coherence. Contributions are made to the literatures on religion and work, hybrid identity work processes and social identities.     

A Context‐sensitive Approach to Analysing Talk in Strategy Meetings

The talk of managers in meetings is central to organizational life and crucial to research in strategic management, as well as managerial and organizational cognition, sensemaking and decision‐making. To achieve full understanding, both the text and the context of discussion require systematic analysis, but most approaches treat context as everything that is known and observed beyond the immediate text. This obscures different readings of the text of meetings. To resolve this problem, the discourse historical approach (DHA) to critical discourse analysis is outlined as a framework within which researchers can analyse the text and context of talk in meetings. The primary contribution of this paper is to isolate four ‘levels of context’ as a heuristic framework within which discursive practices, strategies and texts can be located. By making explicit the levels of contextual analysis that are implicit in other methods, and illustrating the DHA using an episode of strategic discussion from a multinational company, this paper shows how researchers can use the approach to analyse the naturally occurring talk of senior managers in meetings, which is arguably the most important but yet under‐explored venue for strategizing.     

Quantile Uncertainty and Value‐at‐Risk Model Risk

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value‐at‐Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of “model risk” in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value‐at‐Risk model risk and compute the required regulatory capital add‐on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value‐at‐Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks.     

Estimating the Effects of a Time‐Limited Earnings Subsidy for Welfare‐Leavers

In the Self Sufficiency Project (SSP) welfare demonstration, members of a randomly assigned treatment group could receive a subsidy for full‐time work. The subsidy was available for 3 years, but only to people who began working full time within 12 months of random assignment. A simple optimizing model suggests that the eligibility rules created an “establishment” incentive to find a job and leave welfare within a year of random assignment, and an “entitlement” incentive to choose work over welfare once eligibility was established. Building on this insight, we develop an econometric model of welfare participation that allows us to separate the two effects and estimate the impact of the earnings subsidy on welfare entry and exit rates among those who achieved eligibility. The combination of the two incentives explains the time profile of the experimental impacts, which peaked 15 months after random assignment and faded relatively quickly. Our findings suggest that about half of the peak impact of SSP was attributable to the establishment incentive. Despite the extra work effort generated by SSP, the program had no lasting impact on wages and little or no long‐run effect on welfare participation.     

Time‐Staged Overtime Staffing for Services with Updated Forecasts and Availabilities

This article develops a framework for staffing in a service environment when multiple opportunities exist for prescheduling overtime prior to the start of a shift. Demand forecasts improve as the shift approaches, while the availability of workers to be scheduled for overtime decreases. First, a single‐shift model is developed and used in computational studies to evaluate the benefits of time‐staged overtime staffing, which include slightly lower costs and significant reductions in unscheduled overtime and outside agents. A multishift model is then developed to consider constraints on consecutive hours worked and minimum rest intervals between shifts. A multishift computational study shows how the benefits of time‐staged overtime staffing depend on problem characteristics when interactions between shifts are considered. The article discusses how single‐shift and multishift models relate to each other and alternative ways the models may be used in practice, including decentralized open shift management and centralized overtime scheduling.     

Interest‐Talk as Access‐Talk: How Interests are Displayed,Made and Down‐played in Management Research

This paper addresses the methodological issue of how researchers gain access and build trust in order to conduct research in organizations. It focuses, in particular, on the role of interests (what actors want or what they stand to gain or lose) in the research relationship. The analysis shows how notions of interests, stake and motive were managed during an action research study in a UK subsidiary of a multinational corporation. The study uses an approach to discourse analysis inspired by the field of discursive psychology to identify four discursive devices: stake inoculation; stake confession; stake attribution; and stake construction. The paper contributes to the understanding of research methodology by identifying the importance of interest‐talk in the process of doing management research.     

Panel Size and Overbooking Decisions for Appointment‐Based Services under Patient No‐Shows

Many service systems that work with appointments, particularly those in healthcare, suffer from high no‐show rates. While there are many reasons why patients become no‐shows, empirical studies found that the probability of a patient being a no‐show typically increases with the patient's appointment delay, i.e., the time between the call for the appointment and the appointment date. This paper investigates how demand and capacity control decisions should be made while taking this relationship into account. We use stylized single server queueing models to model the appointments scheduled for a provider, and consider two different problems. In the first problem, the service capacity is fixed and the decision variable is the panel size; in the second problem, both the panel size and the service capacity (i.e., overbooking level) are decision variables. The objective in both cases is to maximize some net reward function, which reduces to system throughput for the first problem. We give partial or complete characterizations for the optimal decisions, and use these characterizations to provide insights into how optimal decisions depend on patient's no‐show behavior in regards to their appointment delay. These insights especially provide guidance to service providers who are already engaged in or considering interventions such as sending reminders in order to decrease no‐show probabilities. We find that in addition to the magnitudes of patient show‐up probabilities, patients' sensitivity to incremental delays is an important determinant of how demand and capacity decisions should be adjusted in response to anticipated changes in patients' no‐show behavior.     

Why Do Established Practices Deinstitutionalize? An Actor‐Centred Approach

Drawing on 63 in‐depth interviews from three American multinationals, we investigate how individual actors negotiate the interplay of insider and outsider pressures on the deinstitutionalization of four employment practices in an institutionally complex setting. Existing institutional theory highlights different degrees of deinstitutionalization, from complete abandonment of practices to partial erosion, with an underlying presumption of organizations and actors striving for stability and stasis. However, the present study finds that actor reconciliation of interacting insider and outsider pressures can result in three distinct phases of deinstitutionalization (complete, partial and negotiated deinstitutionalization), which crucially coexist, suggesting perpetual instability and change. The authors conceptualize the individual‐level enabling conditions for each of these different phases of deinstitutionalization, highlighting a range of actor responses as well as differences in how actors exercise agency across each phase. Examining actor negotiation of the interplay of insider and outsider pressures improves our understanding of how individuals engage in differential institutional work when responding to practice deinstitutionalization.     

Over‐the‐Counter Markets

We study how intermediation and asset prices in over‐the‐counter markets are affected by illiquidity associated with search and bargaining. We compute explicitly the prices at which investors trade with each other, as well as marketmakers' bid and ask prices, in a dynamic model with strategic agents. Bid–ask spreads are lower if investors can more easily find other investors or have easier access to multiple marketmakers. With a monopolistic marketmaker, bid–ask spreads are higher if investors have easier access to the marketmaker. We characterize endogenous search and welfare, and discuss empirical implications.     

Vote‐Buying and Reciprocity

While vote‐buying is common, little is known about how politicians determine who to target. We argue that vote‐buying can be sustained by an internalized norm of reciprocity. Receiving money engenders feelings of obligation. Combining survey data on vote‐buying with an experiment‐based measure of reciprocity, we show that politicians target reciprocal individuals. Overall, our findings highlight the importance of social preferences in determining political behavior.     

The Impact of Trade on Intra‐Industry Reallocations and Aggregate Industry Productivity

This paper develops a dynamic industry model with heterogeneous firms to analyze the intra‐industry effects of international trade. The model shows how the exposure to trade will induce only the more productive firms to enter the export market (while some less productive firms continue to produce only for the domestic market) and will simultaneously force the least productive firms to exit. It then shows how further increases in the industry's exposure to trade lead to additional inter‐firm reallocations towards more productive firms. The paper also shows how the aggregate industry productivity growth generated by the reallocations contributes to a welfare gain, thus highlighting a benefit from trade that has not been examined theoretically before. The paper adapts Hopenhayn's (1992a) dynamic industry model to monopolistic competition in a general equilibrium setting. In so doing, the paper provides an extension of Krugman's (1980) trade model that incorporates firm level productivity differences. Firms with different productivity levels coexist in an industry because each firm faces initial uncertainty concerning its productivity before making an irreversible investment to enter the industry. Entry into the export market is also costly, but the firm's decision to export occurs after it gains knowledge of its productivity.     

Point‐of‐Dispensing Location and Capacity Optimization via a Decision Support System

Dispensing of mass prophylaxis can be critical to public health during emergency situations and involves complex decisions that must be made in a short period of time. This study presents a model and solution approach for optimizing point‐of‐dispensing (POD) location and capacity decisions. This approach is part of a decision support system designed to help officials prepare for and respond to public health emergencies. The model selects PODs from a candidate set and suggests how to staff each POD so that average travel and waiting times are minimized. A genetic algorithm (GA) quickly solves the problem based on travel and queuing approximations (QAs) and it has the ability to relax soft constraints when the dispensing goals cannot be met. We show that the proposed approach returns solutions comparable with other systems and it is able to evaluate alternative courses of action when the resources are not sufficient to meet the performance targets.     

Strongly Consistent Self‐Confirming Equilibrium

Fudenberg and Levine (1993a) introduced the notion of self‐confirming equilibrium, which is generally less restrictive than Nash equilibrium. Fudenberg and Levine also defined a concept of consistency, and claimed in their Theorem 4 that with consistency and other conditions on beliefs, a self‐confirming equilibrium has a Nash equilibrium outcome. We provide a counterexample that disproves Theorem 4 and prove an alternative by replacing consistency with a more restrictive concept, which we call strong consistency. In games with observed deviators, self‐confirming equilibria are strongly consistent self‐confirming equilibria. Hence, our alternative theorem ensures that despite the counterexample, the corollary of Theorem 4 is still valid.     

Modeling Imbalanced Economic Recovery Following a Natural Disaster Using Input‐Output Analysis

Input‐output analysis is frequently used in studies of large‐scale weather‐related (e.g., Hurricanes and flooding) disruption of a regional economy. The economy after a sudden catastrophe shows a multitude of imbalances with respect to demand and production and may take months or years to recover. However, there is no consensus about how the economy recovers. This article presents a theoretical route map for imbalanced economic recovery called dynamic inequalities. Subsequently, it is applied to a hypothetical postdisaster economic scenario of flooding in London around the year 2020 to assess the influence of future shocks to a regional economy and suggest adaptation measures. Economic projections are produced by a macro econometric model and used as baseline conditions. The results suggest that London's economy would recover over approximately 70 months by applying a proportional rationing scheme under the assumption of initial 50% labor loss (with full recovery in six months), 40% initial loss to service sectors, and 10–30% initial loss to other sectors. The results also suggest that imbalance will be the norm during the postdisaster period of economic recovery even though balance may occur temporarily. Model sensitivity analysis suggests that a proportional rationing scheme may be an effective strategy to apply during postdisaster economic reconstruction, and that policies in transportation recovery and in health care are essential for effective postdisaster economic recovery.     

Near‐Misses and Future Disaster Preparedness

Disasters garner attention when they occur, and organizations commonly extract valuable lessons from visible failures, adopting new behaviors in response. For example, the United States saw numerous security policy changes following the September 11 terrorist attacks and emergency management and shelter policy changes following Hurricane Katrina. But what about those events that occur that fall short of disaster? Research that examines prior hazard experience shows that this experience can be a mixed blessing. Prior experience can stimulate protective measures, but sometimes prior experience can deceive people into feeling an unwarranted sense of safety. This research focuses on how people interpret near‐miss experiences. We demonstrate that when near‐misses are interpreted as disasters that did not occur and thus provide the perception that the system is resilient to the hazard, people illegitimately underestimate the danger of subsequent hazardous situations and make riskier decisions. On the other hand, if near‐misses can be recognized and interpreted as disasters that almost happened and thus provide the perception that the system is vulnerable to the hazard, this will counter the basic “near‐miss” effect and encourage mitigation. In this article, we use these distinctions between resilient and vulnerable near‐misses to examine how people come to define an event as either a resilient or vulnerable near‐miss, as well as how this interpretation influences their perceptions of risk and their future preparedness behavior. Our contribution is in highlighting the critical role that people's interpretation of the prior experience has on their subsequent behavior and in measuring what shapes this interpretation.     

Incorporating Time‐Dose‐Response into Legionella Outbreak Models

A novel method was used to incorporate in vivo host–pathogen dynamics into a new robust outbreak model for legionellosis. Dose‐response and time‐dose‐response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best‐fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best‐fit TDR from the murine dosing study was the beta‐Poisson with exponential‐reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non‐time‐dependent distributions to explore the performance of the time‐dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host‐pathogen system.