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The purpose of this paper is to propose a method integrating fault tree analysis and optimization model to allocate response budget from the preventive and protective perspectives.

The proposed method consists of two main steps. The first step is to analyze and calculate the probability and the loss of the risk. The second step is to build an optimization model for allocating response budget.

First, there exists an optimal response budget. Second, risk protection is preferred to risk prevention when the total budget is limited. Third, the protective budget should be first invested for the consequence event with greatest expected loss. Fourth, the preventive budget should be first allocated to the risk cause with highest occurrence probability that belongs to the OR set in the fault tree.

Managerially, our results indicate that project managers (PMs) should make a tradeoff between the budget invested for risk response and reduced expected loss of the risk. Then, in the case of inadequate response budget, PMs should pay more attention to risk protection and cope with the event that can cause severe loss. In addition, under this circumstance, PMs had to better allocate the risk preventive budget in proper order.

Project risk response is a critical issue in project risk management as PMs can take actions actively to cope with project risks in this phase. Effective risk response, in general, requires financial support in practice, and reasonable allocation of the total budget among risk response strategies can produce better response effects.

This research aims to explore the nature of Chinese students' mental health information needs and to identify the online resources they use to meet those needs.

Data was collected from three Chinese research-oriented universities using semi-structured interviews and a survey. Twenty-five university students with varied backgrounds were selected for semi-structured interviews to explore the triggers and nature of their needs. Then, printed and online questionnaires were distributed to undergraduate and postgraduate students and 541 valid responses were processed for descriptive statistical analysis and variance analysis.

The following findings were incurred. First, the triggers of university students' mental health information needs mainly are mental health being in the news, personal interest in gaining mental health knowledge, mental health issues, required formal learning and preparation for mental health counselling. Second, eleven types of information are used, with an emphasis on employment pressure, study stress and self-understanding. Third, mental health information needs differ with mental health status and some social-demographic factors (including gender, urban or rural origin and educational stage). Fourth, information needs can be characterized as dynamic; complex and diverse but concentrated on a few types; ambiguous and hard for participants to define; private; stigmatized; self-dependent and substitutable. Fifth, Internet sources used to meet such needs are mainly search engines, Question and Answer platforms, public social media platforms. Finally, a model of mental health information needs was built based on the above findings to map the whole process from what triggers a need, to the content and characteristics of information need, and online resources used to meet those needs.

The paper provides suggestions for university mental health services in developing more tailored knowledge contents via effective delivery methods to meet diverse needs of student groups.

This research is novel in using empirical data to build a holistic model that captures the context and the nature of mental health information needs of university students.

Using the remarkable olfaction ability, insects can sense trace amounts of host plant volatiles that are notorious for causing severe damage to fruits and vegetables and in consequence the industry. The purpose of the paper is to investigate the interactions between olfactory proteins, odorant-binding proteins (OBPs) and host plant volatiles through the developed olfactory biosensors. It might be helpful to develop novel pest control strategies.

Using the successfully expressed and purified OBPs of the oriental fruit fly Bactrocera dorsalis, a biosensor was developed by immobilizing the proteins on interdigitated electrodes through nitrocellulose membrane. Based on electrochemical impedance sensing, benzaldehyde emitted by the host plants, such as Beta vulgaris, was detected, which could be used to investigate and analyze the mechanisms of pests’ sense of chemical signals. The relative decreases of charge transfer resistances of the sensor were proportional to the odorant concentrations from 10⁻⁷ M to 10⁻³ M. Meanwhile, the interactions between OBPs and benzaldehyde were studied through the process of molecular docking.

The paper provides a pest OBPs-based biosensor that could sensitively detect the host odorants benzaldehyde. Meanwhile, the most related amino acids of OBPs that bind to host plant volatiles can be distinguished with molecular docking.

An olfactory biosensor was developed to explore interactions and mechanism between the pest OBPs and benzaldehyde, which showed promising potentials for small organic molecule sensing. Simultaneously, it might be helpful for novel pest control strategies.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

The purpose of this paper is to propose a method to address the problem of selecting risk response actions (RRAs) considering the risk dependency that is seldom considered in the existing studies.

First, a method based on the Measuring Attractiveness by a Categorical-Based Evaluation Technique (MACBETH) is proposed to measure the dependencies between the risks, and then a preference coefficient denoting the relative importance of the risk dependency is introduced. Besides, an exponential utility function is used to describe the project manager’s (PM) risk-averse behaviour. Finally, a mathematical model that incorporates the risk dependency and risk preference of the PM is constructed for selecting the RRAs.

Risk dependency plays an important role in the process of RRA selection. First, more expected utility can be obtained when the risk dependency is considered. Second, more attention should be paid to the risk dependency for coping with critical risks when the budget is tight.

This method can be applied to determine the RRAs when the risk dependency exists between the project risks.

This paper proposes a model to select RRAs with consideration of the risk dependency, which is an important issue from a theoretical as well as a practical perspective in project risk management.

This research investigates how and why firms adopt inclusive diversity activities, identifying the mechanisms behind firms involved in lesbian, gay, bisexual and transgender (LGBT)–friendly pursuits. By integrating resource dependence theory, institutional theory and stakeholder theory, the authors argue that a firm's LGBT friendliness is affected by marketing orientation and the external political environment.

This study uses the Corporate Equality Index, as reported by the Human Rights Campaign, of 460 (1,540 firm-year observations) firms in the United States between 2006 and 2019.

This study finds a significant, positive relationship between a firm's marketing orientation and LGBT-friendly activities. This research also determines that this relationship is weakened by state-level diversity policies and country-level political uncertainty.

The study results provide unique theoretical and practical implications for the debate on inclusive corporate policy in similar global markets.

This study aims to explore the impact of ecosystem-related digital decoupling capability (DDC) and digital integrative capability (DIC) on manufacturing firms’ radical service innovation (RSI) and the moderating effect of strategic flexibility, specifically resource flexibility (RF) and culture flexibility (CF).

This study employed empirical survey data collected from 238 Chinese manufacturing firms to test all hypotheses through hierarchical multiple regression analyses.

DDC and DIC have positive effects on RSI, with DDC exerting a stronger impact. RF and CF strengthen the positive effect of DIC on RSI, whereas CF diminishes DDC’s positive effect on RSI, and RF does not moderate this effect.

Manufacturing firms should prioritize developing ecosystem-related DDC and DIC to drive RSI, especially DDC. Managers should improve firms’ RF and CF when leveraging DIC to drive RSI. However, they should minimize the negative impact of CF when leveraging DDC to drive RSI.

This study shifts the service innovation capabilities from the firm to the ecosystem level, opening a new perspective for exploring RSI’s driving mechanism. With RF and CF as the moderators, the findings reveal the contingent impact mechanism of ecosystem-related digital capabilities on RSI, which provides profound insights into the complex role of strategic flexibility in the new contexts.

Despite a growing number of manufacturing firms actively collaborating with ecosystem members aiming for advanced service solutions, it remains unclear how digital collaboration capability (DCC) affects incremental service innovation (ISI) and radical service innovation (RSI) in the context of ecosystems. Drawing on dynamic capabilities theory and resource orchestration theory, this study aims to investigate the impacts of DCC on ISI/RSI and examine the mediating role of organizational agility (OA).

In this empirical paper, the authors obtained questionnaire data from 238 Chinese manufacturing firms embedded in the ecosystems. Then, the authors examined all the hypotheses through hierarchical regression analyses.

The empirical evidence indicates that DCC has a distinct effect on ISI and RSI. DCC positively affects ISI, whereas DCC shows an inverted U-shaped effect on RSI. In addition, OA mediates the positive effect of DCC on ISI within a certain range, whereas OA always mediates the inverted U-shaped effect of DCC on RSI.

This study enriches and extends existing research on DCC and service innovation by elucidating the heterogeneous effects of DCC on ISI/RSI and the complicated mediating role of OA. This study also has practical implications for manufacturing firms to revisit their collaboration capability and agility to boost ISI/RSI in the context of ecosystems.

This paper aims to investigate the impacts of uncertain online reviews on product prices and profits of two competitive retailers.

First, the authors develop a game-theoretical model to determine the optimal product prices and profits considering uncertain online reviews. Afterwards, to examine the effects of the uncertain online reviews, they compare the equilibrium solutions with those of the game-theoretical models of deterministic online reviews and no online reviews, respectively.

Uncertain online reviews play a significant role in product price optimization and profit maximization. In the quality-dominates-fit case, both retailers will lower their product prices in response to the uncertain online reviews. And the uncertain online reviews would hurt the two retailers. Conversely, in the fit-dominates-quality case, the presence of uncertain online reviews will encourage both retailers to raise their product prices. And the two retailers can still benefit from the online reviews. With the increase in consumer uncertainty about online reviews, both retailers might raise their product prices, thus generating higher profits.

Managerially, the results indicate that in the quality-dominates-fit case, when consumers are uncertain about online reviews, it might be better for retailers to abandon the online review system; however, in the fit-dominates-quality case, both retailers could still benefit from the uncertain online reviews through product price optimization. Therefore, the presence of an online review system could be beneficial.

This paper develops a game-theoretical model to help competitive retailers optimize their price strategies and achieve profit maximization considering uncertain online reviews.

This study aims to examine the potential of Information Ethics (IE) to serve as a coherent ethical foundation for the library and information science profession (LIS profession).

This study consists of two parts: the first part present IE’s central theses and the main critiques it has received; the second part offers the authors' own evaluation of the theory from the LIS perspective in two steps: (1) assessing its internal consistency by testing its major theses against each other; (2) assessing its utility for resolving frequently debated LIS ethical dilemmas by comparing its solutions with solutions from other ethical theories.

This study finds that IE, consisting of an informational ontology, a fundamental ethical assertion and a series of moral laws, forms a coherent ethical framework and holds promising potential to serve as a theoretical foundation for LIS ethical issues; its inclusion of nonhuman objects as moral patients and its levels of abstraction mechanism proved to be particularly relevant for the LIS profession. This study also shows that, to become more solid an ethical theory, IE needs to resolve some of its internal contradictions and ambiguities, particularly its conceptual conflations between internal correctness, rightness and goodness; between destruction, entropy and evil; and the discrepancy between its deontological ethical assertion and its utilitarian moral laws.

This study alerts LIS professionals to the possibility of having a coherent ethical foundation and the potential of IE in this regard.

This study provides a systemic explication, evaluation and field test of IE from the LIS perspective.