Empirical investigation of alternate cumulative capability models: a multi-method approach

Quality (Q), delivery (D), flexibility (F) and cost (C) may reinforce each other to form specific models of cumulative capability. Previous empirical studies reveal two dominant models of cumulative capabilities (Q–D–F–C and Q–D–C–F) without testing whether other models could better fit their data. The present study fulfils this gap and conducts a comparative analysis by testing various models of cumulative capabilities based on a survey of 368 Thai manufacturing plants, and concludes that Q–D–C–F is the best-fit model and further extends the models to reveal ‘simultaneous’ cumulative capability. The contributions are threefold. First, multiple methods are applied to robustly search for the best-fit model. Second, direct and indirect links between capabilities are revealed to add insights into the cumulative reinforcement patterns among capabilities. Third, we show that the widely accepted sand-cone model (Q–D–F–C) and competitive progression theory are not necessarily the dominant approaches for explaining cumulative capability patterns of manufacturers, especially from an emerging country. The results are also significant for practitioners as they understand how capabilities such as quality and delivery can simultaneously improve the next sequential capability.     

Use of Fuzzy Evidential Reasoning in Maritime Security Assessment

Over the last few years, there has been a growing international recognition that the security performance of the maritime industry needs to be reviewed on an urgent basis. A large number of optional maritime security control measures have been proposed through various regulations and publications in the post-9/11 era. There is a strong need for a sound and generic methodology, which is capable of taking into account multiple selection criteria such as the cost effectiveness of the measures based on reasonable security assessment. The use of traditional risk assessment and decision-making approaches to deal with potential terrorism threats in a maritime security area reveals two major challenges. They are lack of capability of analyzing security in situations of high-level uncertainty and lack of capability of processing diverse data in a utility form suitable as input to a risk inference mechanism. To deal with such difficulties, this article proposes a subjective security-based assessment and management framework using fuzzy evidential reasoning (ER) approaches. Consequently, the framework can be used to assemble and process subjective risk assessment information on different aspects of a maritime transport system from multiple experts in a systematic way. Outputs of this model can also provide decisionmakers with a transparent tool to evaluate maritime security policy options for a specific scenario in a cost-effective manner.     

Spatial Risk Assessment Across Large Landscapes with Varied Land Use: Lessons from a Conservation Assessment of Military Lands

Spatial decision-support tools are necessary for assessment and management of threats to biodiversity, which in turn is necessary for biodiversity conservation. In conjunction with the U.S. Geological Survey-Biological Resources Division's Species at Risk program, we developed a GIS-based spatial decision-support tool for relative risk assessments of threats to biodiversity on the U.S. Army's White Sands Missile Range and Fort Bliss (New Mexico and Texas) due to land uses associated with military missions of the two bases. The project tested use of spatial habitat models, land-use scenarios, and species-specific impacts to produce an assessment of relative risks for use in conservation planning on the 1.2 million-hectare study region. Our procedure allows spatially explicit analyses of risks to multiple species from multiple sources by identifying a set of hazards faced by all species of interest, identifying a set of feasible management alternatives, assigning scores to each species for each hazard, and mapping the distribution of these hazard scores across the region of interest for each combination of species/management alternatives. We illustrate the procedure with examples. We demonstrate that our risk-based approach to conservation planning can provide resource managers with a useful tool for spatial assessment of threats to species of concern.     

A Hierarchical Product Development Planning Framework

Uncertainty in new product development (NPD) planning embraces market, creative, technological, and process dimensions to a much greater extent than in non‐NPD project planning. Yet, NPD management is becoming increasingly decentralized, both within the firm and across the supply chain. Hence, planning for NPD uncertainty often results in path‐dependent scenarios cutting across the strategic, tactical, and operational levels of planning. To coordinate this resulting complexity, we propose a stochastic hierarchical product development planning framework with multiple recourses, i. e., corrective actions, to maximize performance across a firm's entire NPD program. We also argue the necessity for a fourth planning level, the infrastructural, that reestablishes norms for market projections, technological forecasts, scheduling, and requirements as latent uncertainty in the environment is continually revealed. An illustration from the automotive industry is presented to demonstrate a deployment of our framework. We additionally discuss the applicability of this framework for managing NPD capabilities over time.     

A Risk Analysis Framework for Cyber Security and Critical Infrastructure Protection of the U.S. Electric Power Grid

The purpose of this article is to introduce a risk analysis framework to enhance the cyber security of and to protect the critical infrastructure of the electric power grid of the United States. Building on the fundamental questions of risk assessment and management, this framework aims to advance the current risk analysis discussions pertaining to the electric power grid. Most of the previous risk-related studies on the electric power grid focus mainly on the recovery of the network from hurricanes and other natural disasters. In contrast, a disproportionately small number of studies explicitly investigate the vulnerability of the electric power grid to cyber-attack scenarios, and how they could be prevented or mitigated. Such a limited approach leaves the United States vulnerable to foreign and domestic threats (both state-sponsored and “lone wolf”) to infiltrate a network that lacks a comprehensive security environment or coordinated government response. By conducting a review of the literature and presenting a risk-based framework, this article underscores the need for a coordinated U.S. cyber security effort toward formulating strategies and responses conducive to protecting the nation against attacks on the electric power grid.     

Uncovering the factors behind new ventures’ international performance: Capabilities,alertness and technological turbulence

This research is based on the perception that the explanation of International New Ventures' (INVs) performance demands a process view, going deeper than the standard approach, in empirical papers, of testing a direct relationship between company-level antecedents and performance. A three-tier model was developed to investigate the process leading to INVs international performance, emphasizing the role of entrepreneurial alertness. Based on the dynamic capabilities framework, entrepreneurial alertness was envisaged as the mediating element between firms' capabilities and their international performance. Empirical research confirmed the hypothesized model. Firms' capabilities (entrepreneurial orientation, foreign market knowledge, and absorptive capacity) significantly influence the level of entrepreneurial alertness, which impacts on the levels of self-reported satisfaction with the company's international performance. The paper makes four contributions to International Entrepreneurship literature. First, it highlights the key role played by entrepreneurial alertness in explaining INVs' international performance. This is convergent with the dynamic capabilities view on firms' ability to sense and seize specific international business opportunities. Second, this study considers entrepreneurial alertness as a capability that is not limited to the entrepreneur, but it is an organizational capability. Third, it shows that entrepreneurial alertness does not exist in the vacuum, is based on a set of base capabilities, namely entrepreneurial orientation, foreign market knowledge, and absorptive capacity, that simultaneously leverage the INVs to sense possible opportunities and constrain the focus of opportunities to international markets, as a key element to foster INVs' higher performance. Fourth, it underlines the role of technological turbulence as a moderator of the relationship between entrepreneurial alertness and INVs' international performance.     

The Impact of Population,Contact, and Spatial Heterogeneity on Epidemic Model Predictions

Our objective was to evaluate the effect that complexity in the form of different levels of spatial, population, and contact heterogeneity has in the predictions of a mechanistic epidemic model. A model that simulates the spatiotemporal spread of infectious diseases between animal populations was developed. Sixteen scenarios of foot‐and‐mouth disease infection in cattle were analyzed, involving combinations of the following factors: multiple production‐types (PT) with heterogeneous contact and population structure versus single PT, random versus actual spatial distribution of population units, high versus low infectivity, and no vaccination versus preemptive vaccination. The epidemic size and duration was larger for scenarios with multiple PT versus single PT. Ignoring the actual unit locations did not affect the epidemic size in scenarios with multiple PT/high infectivity, but resulted in smaller epidemic sizes in scenarios using multiple PT/low infectivity. In conclusion, when modeling fast‐spreading epidemics, knowing the actual locations of population units may not be as relevant as collecting information on population and contact heterogeneity. In contrast, both population and spatial heterogeneity might be important to model slower spreading epidemic diseases. Our findings can be used to inform data collection and modeling efforts to inform health policy and planning.     

Strategic planning—Which style do you need?

Strategic planning is now a large and diverse activity practised in many different kinds of organizations. This article provides an overview of the field with a summary of the five main schools of thought each with its own business philosophy and a range of practical approaches and techniques. These basic styles are concerned with planning as a central control system, a framework for innovation, an organizational change process, a political activity, and a way of exploring the future. Most planning systems have a dominant style or focus and this emphasis needs to be adjusted in response to changes which are occurring continually in the organization and in the external environment. The article is designed to help the senior manager or corporate planner to assess the state of planning in his organization and to see where there are important gaps in the enterprise's capability for planning which might be filled by the launching of new initiatives. The article also offers an agenda of approaches for consideration by the executive who wishes to move his enterprise from a conventional 5-year planning and budgeting system towards a more comprehensive process of managing organizational change and development.     

Integrated planning for health care organizations, especially hospitals

Planning in health care organizations is of considerable current interest in this country. Furthermore, effective planning processes require, as a necessary condition for that effectiveness, development within a framework which considers the organizational, managerial and service delivery environment.This paper examines the concept of planning in relation to health care organizations. Through an examination of the effects which proper planning can have upon industrial organizations the authors analyze the possible impacts of planning procedures upon health care institutions. Their analysis leads to certain tentative conclusions as to appropriate organizational structure which could support effective planning. Whilst the authors have yet to test their hypothesis the conclusion they draw from their initial analysis are worthy of further investigation.     

Health insurance system and resilience to epidemics

We theoretically analyze the resilience (efficiency) of health insurance systems and diverse factors including trace and test technology, infection and contagion rates, and social distancing/lockdown policy, in coping with contagious diseases like COVID-19. Our findings can be summarized as follows. First, public insurance is more resilient than market insurance, as the former's investment in test technology is made at the social optimum, whereas the latter's investment is less. The decentralized behavior of competing insurers leads to a less resilient outcome. Second, resilience decreases as the market becomes more competitive because the externality effect becomes more severe. Third, a higher contagion rate, a more cost-efficient test technology or a higher initial infection rate unless it is not too high, leads to a higher test accuracy level. Fourth, the socially optimal social distancing/lockdown policy is determined by comparison between its relative costs and the benefit from contagion reduction.     

Three dimensions of COVID-19 risk perceptions and their socioeconomic correlates in the United States: A social media analysis

Social media analysis provides an alternate approach to monitoring and understanding risk perceptions regarding COVID-19 over time. Our current understandings of risk perceptions regarding COVID-19 do not disentangle the three dimensions of risk perceptions (perceived susceptibility, perceived severity, and negative emotion) as the pandemic has evolved. Data are also limited regarding the impact of social determinants of health (SDOH) on COVID-19-related risk perceptions over time. To address these knowledge gaps, we extracted tweets regarding COVID-19-related risk perceptions and developed indicators for the three dimensions of risk perceptions based on over 502 million geotagged tweets posted by over 4.9 million Twitter users from January 2020 to December 2021 in the United States. We examined correlations between risk perception indicator scores and county-level SDOH. The three dimensions of risk perceptions demonstrate different trajectories. Perceived severity maintained a high level throughout the study period. Perceived susceptibility and negative emotion peaked on March 11, 2020 (COVID-19 declared global pandemic by WHO) and then declined and remained stable at lower levels until increasing once again with the Omicron period. Relative frequency of tweet posts on risk perceptions did not closely follow epidemic trends of COVID-19 (cases, deaths). Users from socioeconomically vulnerable counties showed lower attention to perceived severity and susceptibility of COVID-19 than those from wealthier counties. Examining trends in tweets regarding the multiple dimensions of risk perceptions throughout the COVID-19 pandemic can help policymakers frame in-time, tailored, and appropriate responses to prevent viral spread and encourage preventive behavior uptake in the United States.     

Is a disease leader attractive? Six tests of whether the COVID-19 pandemic affected follower preferences for attractiveness,health and other traits in political and non-political leaders

Attractive political candidates receive more votes on Election Day compared to their less attractive competitors. One well-cited theoretical account for this attractiveness effect (White et al., 2013) holds that it reflects an adaptive psychological response to disease threats. Voters are predicted to upregulate preferences for attractiveness because it constitutes a cue to health. The global COVID-19 pandemic constitutes an ecologically relevant and realistic setting for further testing this prediction. Here, we report the results from six tests of the prediction based on two large and nationally representative surveys conducted in Denmark (n = 3297) at the outbreak of the pandemic and one year later. Utilizing experimental techniques, validated individual difference measures of perceived disease threat and geographic data on COVID-19 severity, we do not find that disease threats like the COVID-19 pandemic upregulate preferences for attractive and healthy political or non-political leaders. Instead, respondents display heightened preferences for health in socially proximate relations (i.e. colleagues). Moreover, individuals who react aversively to situations involving risks of pathogen transmission (scoring high in Germ Aversion) report higher importance of a wide range of leadership traits, rather than for health and attractiveness in particular. Results are discussed in relation to evolutionary accounts of leadership and followership.     

CEO health

Using comprehensive data on 28 cohorts in Sweden, we analyze CEO health and its determinants and outcomes. We find CEOs are in much better health than the population and on par with other high-skill professionals. These results apply in particular to mental health and to CEOs of larger companies. We explore three mechanisms that can account for CEOs’ robust health. First, we find health predicts appointment to a CEO position. Second, the CEO position has no discernible impact on the health of its holder. Third, poor health is associated with greater CEO turnover. Here, both contemporaneous health and health at the time of appointment matter. Poor CEO health also predicts poor firm outcomes. We find a statistically significant association between mental health and corporate performance for smaller-firm CEOs, for whom a one standard deviation deterioration in mental health translates into a performance reduction of 6% relative to the mean.     

A Computational Framework for Prime Implicants Identification in Noncoherent Dynamic Systems

Dynamic reliability methods aim at complementing the capability of traditional static approaches (e.g., event trees [ETs] and fault trees [FTs]) by accounting for the system dynamic behavior and its interactions with the system state transition process. For this, the system dynamics is here described by a time‐dependent model that includes the dependencies with the stochastic transition events. In this article, we present a novel computational framework for dynamic reliability analysis whose objectives are i) accounting for discrete stochastic transition events and ii) identifying the prime implicants (PIs) of the dynamic system. The framework entails adopting a multiple‐valued logic (MVL) to consider stochastic transitions at discretized times. Then, PIs are originally identified by a differential evolution (DE) algorithm that looks for the optimal MVL solution of a covering problem formulated for MVL accident scenarios. For testing the feasibility of the framework, a dynamic noncoherent system composed of five components that can fail at discretized times has been analyzed, showing the applicability of the framework to practical cases.     

Leading well: Challenges to researching leadership in occupational health psychology – and some ways forward

ABSTRACT

Studies on the effects of leadership in occupational health psychology build on the assumption that leaders influence their followers’ health and well-being. Although this assumption has received support, this introductory paper to a special issue of Work & Stress on leadership argues that a number of questions regarding leadership and follower health and well-being remain unanswered. We identify four issues that we argue warrant further attention. First, what is “good” leadership? Particular leadership types are associated with increases in employee performance, but since this will involve higher effort expenditure, adverse outcomes for employee health are to be expected. Although many types of leadership are associated with favourable outcomes, we still need to identify the leadership characteristics can be identified that account for these positive outcomes. Second, how can good leadership be promoted? There is a need to develop interventions that are effective in promoting desirable leadership styles. Third, what are the inter-mediate and long-term effects of leadership on follower health? Finally, we need to understand the boundary conditions for good leadership, including the resources available to leaders. Based on these considerations, we conclude that further research is needed to fully understand the effects of leadership on employee health and well-being.     

Danger control and fear control during public health emergencies: Considering the roles of fear and hope in the EPPM across different levels of trust

Public health emergencies pose considerable threats to global health and safety. The control of these emergencies requires the efforts of healthcare professionals and calls for the public to take protective actions. The present study not only puts fear back in the extended parallel process model (EPPM) but also considers another similarly productive emotion: hope. We examined the mechanisms behind the effects of four cognitive perceptions on protective actions (i.e., danger control) and information avoidance (i.e., fear control). A national online survey was conducted with 1676 participants during the outbreak of COVID-19 in China from February 1 to 29, 2020. The results revealed that perceived severity and susceptibility could lead to fear, positively affecting protective actions. On the other hand, perceived response efficacy and self-efficacy induced hope, which was positively associated with protective actions but negatively associated with information avoidance. Furthermore, the mechanisms behind the relationships among cognitions, emotions, and behaviors varied across levels of trust in healthcare systems.     

Integrating multicriteria decision analysis and scenario planning—Review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of “metacriteria” (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country.     

Managing Knowledge for Innovation

This paper describes a technique for identifying knowledge gaps in innovative firms. Gaps occur between existing knowledge and knowledge requirements and particularly occur when a firm is trying to introduce new processes or products. The authors were involved in a knowledge management project in a UK telecoms company and report on a framework that they developed that assists in examining the dimensions of knowledge gaps so that they may be bridged. This technique also allows the firm to measure the vulnerability of its knowledge bases.     

Improving human resources for health planning in developing economies

There is a universal consensus that human resources represent the heart and soul of effective health systems everywhere. However, despite this consensus, human resource planning in low income countries remains a neglected, often poorly implemented and ineffective component of health-system development. The planning exercises that do take place are often inefficient, use inappropriate planning models or fail to adequately prioritize human resource investment decisions. This article briefly discusses possible reasons why this failure occurs and describes four key steps that can help health system planners more effectively prioritize and link human resource for health investment decisions to health system strategy and programmatic initiatives. Implications for human resource development practice and national human resource development are discussed.     

IT security planning under uncertainty for high-impact events

While many IT security incidents result in relatively minor operational disruptions or minimal recovery costs, occasionally high-impact security breaches can have catastrophic effects on the firm. Unfortunately, measuring security risk and planning for countermeasures or mitigation is a difficult task. Past research has suggested risk metrics which may be beneficial in understanding and planning for security incidents, but most of these metrics are aimed at identifying expected overall loss and do not directly address the identification of, or planning for, sparse events which might result in high-impact loss. The use of an upper percentile value or some other worst-case measure has been widely discussed in the literature as a means of stochastic optimization, but has not been applied to this decision domain. A key requirement in security planning for any threat scenario, expected or otherwise, is the ability to choose countermeasures optimally with regard to tradeoffs between countermeasure cost and remaining risk. Most of the planning models in the literature are qualitative, and none that we are aware of allow for the optimal determination of these tradeoffs. Therefore, we develop a model for optimally choosing countermeasures to block or mitigate security attacks in the presence of a given threat level profile. We utilize this model to examine scenarios under both expected threat levels and worst-case levels, and develop budget-dependent risk curves. These curves demonstrate the tradeoffs which occur if decision makers divert budgets away from planning for ordinary risk in an effort to mitigate the effects of potential high-impact outcomes.