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Considering sustainability and resilience together is crucial in food supply chain (FSC) management, as it ensures a balanced approach that meets environmental, economic and social needs while maintaining the system's capacity to withstand disruptions. Towards this, a multi-objective optimisation model is proposed in this study to create an integrated sustainable and resilient FSC. The proposed model employs four objective functions – each representing a dimension of sustainability and one for resilience and utilises an augmented ϵ-constraint method for solving. The findings highlight the interplay between sustainability aspects and resilience, illustrating that overemphasis on any single dimension can adversely affect others. Further, the proposed model is applied to the case of Indian mango pulp supply chain and several inferences are derived. The proposed model would assist decision-makers in making a well-balanced choice based on sustainability and resilience considerations.

This paper (Part 2 of 2) aims to expand the previously developed performance assessment model (PAM) into a decision support system (DSS) to produce optimized decisions on rehabilitation of facilities.

The research includes a comprehensive PAM that integrates analytical hierarchy process-multi attribute utility theory methods for the physical, operational, and environmental aspects of the mosque, as described in Part 1 of the study. An optimized intervention tool is added to the PAM to complete the DSS development. The tool determines the optimum maintenance decisions that are in line with the budget and condition criticality. The deterioration measures are created using a deterministic straight-line extrapolation technique, and the intervention actions used in the optimization are specified through literature review and in-depth interviews with 11 experts. The optimization model was simplified into a user-friendly visual basic application and applied to an existing facility case study depicting its useful functionality.

The optimization model recommendation of interventions recovered the overall condition rating index (CRI) of the facility while maintaining budget constraints. The CRI in the first approach (minimum budget to achieve acceptable overall performance) was improved from 6.5 to 7.76, costing 275,850 SAR. While the second approach (Maximum recovery with a selected budget constraint, 300,000 SAR in this case) CRI was improved from 6.5 to 8.3, costing 299,850 SAR.

The presented DSS in this paper offers a tool that enables the rehabilitation and overall management of any facility by its managers. The DSS can also be further customized to fit the facility manager’s specific strategies and achieve desired objectives.

The purpose of this study is to present a system dynamic (SD)-based remanufacturing economic analysis model of used automobile engine under two recycling modes. The authors will compare the remanufacturing cost, sales profit and sales revenue from time and space dimensions incurred in different recycling modes in the long run.

The remanufacturing economic analysis model is based on SD methodology. The authors can simulate the relations of impact factors on automobile engine recycling and remanufacturing and further analyze and compare the cost, sales profit and sales revenue incurred in different recycling modes in the long term.

Sinotruk Steyr engine remanufacturing in Shandong province is taken as the research case subject. The revenue, cost and profit under the two recycling modes from 2015 to 2035 are analyzed and compared. The results show that different recycling modes have significant varying influence on the economy of engine remanufacturing.

This economic analysis model can provide a method reference to decide the recycling mode for auto components and other product remanufacturing. Moreover, this model can guide and support the sustainable development of remanufacturing industry.

This paper extends the authors’ previous research work investigating resilience for municipal infrastructure from an asset management perspective. Therefore, this paper aims to formulate a pavement resilience index while incorporating asset management and the associated resilience indicators from the authors’ previous research work.

This paper introduces a set of holistic-based key indicators that reflect municipal infrastructure resiliency. Thenceforth, the indicators were integrated using the weighted sum mean method to form the proposed resilience index. Resilience indicators weights were determined using principal components analysis (PCA) via IBM SPSS®. The developed framework for the PCA was built based on an optimization model output to generate the required weights for the desired resilience index. The output optimization data were adjusted using the standardization method before performing PCA.

This paper offers a mathematical approach to generating a resilience index for municipal infrastructure. The statistical tests conducted throughout the study showed a high significance level. Therefore, using PCA was proper for the resilience indicators data. The proposed framework is beneficial for asset management experts, where introducing the proposed index will provide ease of use to decision-makers regarding pavement network maintenance planning.

The resilience indicators used need to be updated beyond what is mentioned in this paper to include asset redundancy and structural asset capacity. Using clustering as a validation tool is an excellent opportunity for other researchers to examine the resilience index for each pavement corridor individually pertaining to the resulting clusters.

This paper provides a unique example of integrating resilience and asset management concepts and serves as a vital step toward a comprehensive integration approach between the two concepts. The used PCA framework offers dynamic resilience indicators weights and, therefore, a dynamic resilience index. Resiliency is a dynamic feature for infrastructure systems. It differs during their life cycle with the change in maintenance and rehabilitation plans, systems retrofit and the occurring disruptive events throughout their life cycle. Therefore, the PCA technique was the preferred method used where it is data-based oriented and eliminates the subjectivity while driving indicators weights.

We develop a credit-risk model to study the informational role of investment in an economy susceptible to large liquidity shocks. Firms' investment decisions carry information about their asset quality, thereby mitigating informational frictions when firms enter bankruptcy. An increase in aggregate investment can reduce the informational value of investment, depressing firms' recovery values. Therefore, policies boosting investment can decrease debt and firm values by reducing the informational value of investment. The presence of debt overhang may enhance firm value by making firms' investment decisions more informative. We present suggestive empirical evidence consistent with model predictions on the relation between firms' investments and recovery rates.

This paper aims to explore the effectiveness of customer inoculation strategies in the context of AI service failures in the hospitality and tourism industries. Furthermore, it examines how these strategies can enhance customer complaint behavior and satisfaction with service recovery, thereby improving the overall service experience.

Four distinct studies were conducted: Study 1 investigated the influence of customer inoculation on complaint behavior post-AI service failure. Study 2 assessed the impact of service remedies on customer satisfaction. Study 3 explored the implications of initial purchase and usage intentions. Finally, Study 4 validated the findings using a large-scale online survey.

The results indicated that customer inoculation significantly increases customer complaint behavior and satisfaction with service remedies following AI service failures. They also showed that this relationship is mediated by psychological distance. Furthermore, customer inoculation positively affects initial purchase and usage intentions, demonstrating effectiveness at various customer engagement stages.

This study enriches the literature on AI hospitality service failure and recovery by introducing the novel concept of customer inoculation. Additionally, it significantly contributes to the inoculation theory literature, which covers diverse fields. Practically, this study proposes an efficient and low-cost strategy for marketers.

This study introduces the concept of customer inoculation in the context of AI service failures, a novel approach in the hospitality and tourism literature. It provides empirical evidence of the efficacy of the strategy, bridging a crucial gap in understanding customer behavior in the face of technological disruptions.

As a company’s corporate social responsibility (CSR) image can protect from the backlash of a service failure, it is important to remind customers of the company’s CSR commitment when a service failure occurs. One novel mechanism for doing so is through a prosocial service recovery. However, explorations of such service recovery strategies are relatively unknown. Thus, this paper aims to examine how recoveries including prosocial elements compare to those only utilizing monetary compensation strategies and to explore boundary conditions for such effects.

This research utilizes an experimental design approach across three studies. Participants were recruited from Amazon’s Mechanical Turk.

This research demonstrates that a recovery including prosocial (vs only monetary) elements can positively impact purchase intent through the firms’ CSR perceptions. The authors show that the benefits of prosocial compensation are contingent on the motivation for visiting a company (e.g. hedonic vs utilitarian) as well as the degree to which the company is perceived as luxurious.

The series of studies provides important theoretical contributions to services marketers by advancing the understanding of novel recovery strategies and demonstrating when companies should initiate such strategies. Implications of the findings and directions for future research are explored.

In response to water scarcity in Sri Lanka, the government is implementing strategies such as rainwater harvesting, efficient irrigation, wastewater treatment and desalination. Initial efforts include the establishment of a desalination plant in Jaffna, with additional plans for the dry zones (DZ). The study aims to comprehensively identify the barriers to establishing desalination plants in the DZ and provide recommendations to mitigate these barriers. Additionally, this research provides valuable insights aimed at minimizing barriers to the construction of future desalination plants within Sri Lanka.

The study used qualitative methods, using an expert survey to identify current and future barriers, along with strategies for overcoming them. The collected data were analysed using the template analysis technique.

Regarding desalination plant establishment, various barriers such as high capital costs, high energy expenses, brine discharge, pollution, emissions, technical challenges, health concerns and waste disposal have been identified. However, specific strategies exist to address and mitigate each of these obstacles.

The study offers recommendations to environmental experts and government on expediting the approval procedures for desalination plants in Sri Lanka’s DZ. Adapted to Sri Lanka’s specific challenges, it highlights strategies and barriers essential for upcoming desalination projects. Furthermore, it emphasizes the financial advantages such as increased production and job creation resulting from establishing desalination facilities.

Through this study, promoting sustainable practices and fostering community involvement, it aims to enhance livelihoods, accelerate economic development and improve overall well-being through reliable access to water. Additionally, the study aims to enhance understanding of the importance of desalination in alleviating water scarcity, promoting community engagement and ultimately facilitating improved living conditions, health outcomes and economic opportunities in Sri Lanka’s DZs.

This study provides crucial direction for decision-makers by highlighting the main barriers to the establishment of desalination plants in Sri Lanka and outlining practical solutions. Implementing these strategies helps meet the region’s increasing water demands, advance sustainable water management, improve the standard of living for nearby communities and promote the socioeconomic development of desalination plants in Sri Lanka’s DZ.

This study examined the links between user-generated content (UGC), dissatisfied customers and second-hand luxury fashion brands. A central premise of luxury fashion brands is the perceived status and privilege of those who own such items. Despite their marketing logic emphasising exclusivity and rarity, they have broadened their reach by integrating new digital marketing practices that increase access to luxury brand-related information and create opportunities for consumers to purchase products through second-hand sellers.

Building on an inductive qualitative study of 59 millennials from three European countries (France, Italy and the UK) and by examining the mediating role of UGC and dissatisfied customers, this paper develops a conceptual framework of three clusters of second-hand luxury fashion goods customers: spiritual consumers, entrepreneurial recoverer consumers and carpe diem consumers.

The proposed SEC framework (spiritual consumers, entrepreneurial recoverer consumers, and carpe diem consumers) illustrates how the emerging themes interconnect with the identified consumers, revealing significant consumer actions and attitudes found in the second-hand luxury goods sector that influence the usage of UGC and its integration into service failure and recovery efforts

This study suggested that the perceptions of consumers seeking second-hand luxury fashion products differ from those who purchase new or never previously owned luxury fashion products. Overall, this research sets the stage for scholars to forge a path forward to enhance the understanding of this phenomenon and its implications for luxury fashion companies.

The global economy is facing a steep challenge from volatility, risk and uncertainty associated with climate change, pandemics, regional conflicts and trade wars which are unprecedented and overlapping. These crises are leading to macro- and microeconomic imbalances. The immediate effects like rising inflation, shortage of energy and fertiliser, food insecurity, loss of jobs and poverty are looming large, leading to existential threat. It is evident that decades of progress are at risk and pursuing sustainable development goals (SDGs) requires dedicated and customised efforts by the governments and other relevant actors, especially in the low- and middle-income countries (LMICS). The concept of circular economy is considered to bring a paradigm shift by reducing the dependence on natural resource extraction and decoupling economic growth from use of natural resources. Bioeconomy is another emerging field which deals with the use of renewable biological resources such as biomass to produce renewable biofuels, bioproducts, and biopower for economic, environmental and social benefits. Circular bioeconomy (CBE) lies at the intersection and is defined as the production of recoverable biological (waste) resources and the conversion of these resources into high-value-added products, such as food, feed, bio-based products and bioenergy. It has been estimated that the economic opportunity for the sector to complement or even substitute conventional ones is estimated to be USD 7.7 trillion by 2030 for food and feed waste products, and energy. CBE is perceived as a pathway for development and has the potential to target different SDGs directly like 6, 7 and 12 and SDGs 2, 3, 11, 12, 13 and 15 indirectly. This study explores the linkages of CBE with the SDG goals and provides recommendations to stimulate the sector.