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Currently, digital technology has been proposed as a new archetype for developing an effective traceability system in the perishable food supply chain (FSC). Implementation of such a system needs significant investment and the burden lies with the members of the supply chain. The purpose of this paper is to examine the impact on the profit of the supply chain members due to the implementation of an effective traceability system with such a large investment. The study also tries to explore the impact of the implementation of such a system by coordination among the members through a cost-sharing mechanism.

A two-level supply chain that comprises a supplier and retailer is analyzed using a game-theoretic approach. The mathematical models are developed considering the scenario for an individual, centralized and both members invest using a cost-sharing mechanism. For each of the models, the impact of product selling price, information sensing price and quality improvement level on profit is analyzed through numerical analysis.

The study reveals that consumer involvement can be a strong motivation for the supply chain members to initiate investment in the traceability system. Further, from an investment perspective cost-sharing model is beneficial compared to the individual investment-bearing model. This mechanism can coordinate as well as benefit the FSC members. However, the model is less beneficial to the centralized model from profit and quality improvement levels.

Food wastage can be less from supplier and retailer perspectives. Moreover, consumers can purchase food items only after verifying their shipping conditions. Consequently the food safety scandals can be reduced remarkably.

Digital technology adoption in the perishable FSC is still considered emerging. The present study helps organizations to implement a traceability system in the perishable FSC through consumer involvement and a cost-sharing mechanism.

THE design and operation of a vibration simulator is described, and measurements of the body resonances of a number of people over the frequency range 1 to 10 c.p.s. for vertical and lateral vibrations are presented. Comfort ratings have been obtained for these vibrations at various levels of acceleration. The response of an aircraft to atmospheric turbulence has been simulated assuming that the aircraft fuselage will vibrate predominantly in one flexible mode. Comfort ratings have been obtained for lateral turbulence, and a comparison has been made between these results and those for sinusoidal vibrations. The effect of random, vertical and lateral vibrations separately on task performance has been measured, also the effect of length of exposure to vibration on task performance for random vertical vibrations at various magnitudes.

The purpose of this study is to find the reliability of the three-component three-phased mission system, which can be repaired by considering the exponential distribution for repair and failure rates in the transitions between the phases based on states with Markov approach. Also, multilevel-phased mission systems are calculated based on states for partially working states.

The reliabilities of the repairable two-level and three-level three-component three-phased mission systems based on states are calculated with the Markov approach. The structure functions are obtained for each phase of the systems, and differential equations are created by the failure and repair of each working state component. These equations are solved using Laplace method.

Reliability values of two-level and three-level three-component three-phased systems with different failure, repair, and time intervals are calculated and compared. The intermediate states that multilevel systems handle differently from two-level systems provide a better investigation of the systems. So, these repairable systems offer transparent information in complex systems like transportation and energy, ensuring appropriate timing and cost for repair operations.

This study is original in terms of calculating the reliability of the repairable phased mission system based on the states using Markov method. It is also important in calculating the reliability of the repairable multilevel phased mission system based on states and making reliability comparisons according to different repair and failure rates, equal and different time intervals.

Upstream suppliers attempt to outsource product after-sales services to midstream third-party service providers while selling the product directly to downstream sellers, forming a networked supply chain. However, a problem of information asymmetry in the market demand among supply chain members exists. The authors investigate the impact of demand information asymmetry among third-party service providers, upstream suppliers and downstream sellers in the supply chain on the supplier's contract selection under the networked framework.

The authors establish a model in which the supplier can use a wholesale price contract and facilitate a signaling game between the third-party service provider and the seller. Conversely, the supplier could use a menu contract to establish an incentive mechanism to solve information asymmetry. The authors propose heuristic algorithms to quickly estimate a supplier's optimal profit.

The results show that when the demand forecasting bias is relatively small, the use of a menu contract by the supplier could eliminate information asymmetry; when the demand forecasting bias is large enough, the signaling mechanism between the third-party service provider and the seller could alleviate the double marginalization effect in the supply chain. Although it is common to solve the asymmetric information problem by establishing incentive mechanisms, the authors found that in the latter case, the supplier is better off when no incentive mechanisms are implemented in the networked supply chain.

This study compares screening and signaling effects and compares firms' profits in both cases.

This paper forms an e-commerce supply chain that include a manufacturer providing products and an online platform providing service. The reselling platform mode and the agent platform mode are considered through an exploration of the manufacturer Stackelberg (MS), vertical Nash (VN), platform Stackelberg (PS) power structures. The purpose of this paper is to explore the pricing and platform service decisions under different platform selling modes and channel power structures.

Based on the game theory models, this paper investigates the interaction between the manufacturer and the online platform under four different scenarios. The optimal solutions of four models are provided. Through comparison analyses, this paper evaluates the impacts of platform selling mode and channel power structure on the pricing and platform service decisions and the members’ profits.

The manufacturer prefers the MS power structure in any platform mode. The online platform prefers the PS (MS) power structure under a low (high) service cost efficiency in the reselling platform mode, while prefers the PS and VN power structures in the agent platform mode. Moreover, the manufacturer prefers the agent (reselling) platform mode under a low (high) service cost efficiency in any power structure. The online platform prefers the reselling platform mode in the MS and PS power structures, while prefers the reselling (agent) platform mode under a low (high) service cost efficiency in the VN power structures.

The analysis result provides important managerial implications that help the supply chain members develop a better understanding of the selection of the platform selling mode and the effect of the channel power structure in the presence of platform service.

This paper aims to suggest a parameter independent and simple speed estimator for primary field-oriented control of a promising electro-mechanical energy conversion device in the form of brushless doubly-fed reluctance machine (BDFRM) drive.

The speed estimation algorithm, in this context, is formulated using a modified secondary winding active power (mPs)-based model reference adaptive system (MRAS). The performance of the proposed estimator is verified through computer aided MATLAB simulation study, compared with conventional active power-based MRAS and further supported with experimental validation using a 1.6 kW BDFRM prototype run by a dSPACE-1103 controller.

The formulation of mPs-MRAS is insensitive to any machine parameters and does not involve any integration/differentiation terms. Thus, any deviation therein does not hinder the performance of the mPs-MRAS-based speed estimator. The proposed speed estimator shows stable behavior for variable speed-constant load torque operation in all the four quadrants.

The formulation of mPs-MRAS is insensitive to any machine parameter and does not involve any integration/differentiation terms.

This study aims to investigate the valuation accuracy of Malaysian initial public offerings (IPOs) by using price-multiple methods.

Cross-sectional data including 467 IPOs listed on the Malaysian stock exchange were used for the period of 2000–2017. This study used univariate ordinary least square (OLS) regression to analyse the relationship between IPOs’ price-multiples and comparable firms’ price-multiples. The test of valuation accuracy was conducted via computing valuation errors by segregating the sample into two groups: fixed-price IPOs and book-built IPOs. Furthermore, multiple OLS regression was used to examine the influence of IPO valuation on underpricing.

The findings of the results suggested that IPOs price-to-earnings (P/E), price-to-book (P/B) and price-to-sales (P/S) multiples were positively related to the median P/E, P/B and P/S multiples of five comparable firms matched by industry and revenues. The P/S multiple was shown to be the most significant valuation method, specifically in book-built IPOs. The findings indicated that those firms that had a lower valuation in comparison to the comparable firms were inclined to underprice their IPOs to allure investors to subscribe IPOs. In addition, book-built IPOs that had fair valuations were inclined to generate higher initial returns for investors.

The findings of this study observed implications for underwriters in avoiding the mis-valuation issue by considering the book-building mechanism.

This study attempted to explore the suitability of the valuation method to value IPOs in Malaysia.

Although the physical environment provides an important context for employees' work, there remain divergent findings regarding how different spatial settings, such as more open or more closed workspaces, impact employees. Employing research on the functions of the physical work environment, we contribute to a growing body of research on employees' interactions with their workspace by developing and measuring the notion of person–space fit (P-S fit). This construct affords examination of the multi-dimensional nature of employees' interactions with their workspaces, to understand how their perceived fit with the key functions of their workspace impacts their experiences and social network activity at work.

We first develop a new P-S fit scale and test its factorial, convergent, discriminant, and incremental validity over other person–environment fit concepts (N = 155). Next, in a naturally-occurring, quasi-field experiment of a workspace change intervention moving employees from predominantly closed workspace to more open workspace (N = 47 pre-move; N = 37 post-move), we examine how changes in both workspace layout and P-S fit impact workers' experiences of their workspaces (needs for task privacy and spaciousness) and collaborative behaviors (social network activity).

Our P-S fit scale consists of theoretically and empirically validated dimensions representing fit with four workspace functions: aesthetic fit; identity fit; instrumental fit; and collaboration fit. Instrumental fit is positively associated with experiences of task privacy, whereas aesthetic fit and identity fit positively associated with experiences of spaciousness, but no forms of fit were related to social network activity. However, the findings show that work-related social network ties tended to decrease, and new ones were less likely to form, in open office spaces.

Contributing to a growing body of research linking person–environment fit literature to workspace design, this study offers a new scale assessing P-S fit and provides some empirical evidence of its importance for understanding the complexity of the employee-work environment interaction.

The purpose of this study is to examine the influence of underwriter reputation on the valuation of Malaysian initial public offerings (IPOs).

This study employed cross-sectional multiple regression models to analyse the relationship between underwriter reputation and IPO valuation that included 466 IPOs listed on Bursa Malaysia from 2000 to 2017.

The results revealed that underwriter reputation had a significant negative association with IPO valuation. Firms that engaged the services of reputable underwriters had their IPO offer prices set lower than the intrinsic values during the listing. After incorporating firms' size, this study found a positive relationship between underwriter reputation and IPO valuation. Big firms (high quality) hired reputable underwriters for certification purposes as issuers were aware that the cost of hiring a reputable underwriter would be justified by increased transparency after listing. Therefore, firms that engaged reputable underwriters had approximately fair values since issuers assumed that the price would be close to the intrinsic value following enhanced transparency post-listing.

Future studies should focus on other non-financial factors, such as auditor reputation.

The present study provides new insights into the certification role of underwriters in valuing IPOs in the Malaysian market.

Product counterfeiting has been ubiquitously observed in various segments of the supply chain. The intrinsic values of brands create more opportunities for counterfeiting. The damaging reputation of such brands leaves them to deal with the fallouts of counterfeits. Hence, such companies address them mainly through legal action, price and quality strategy. However, consumer characteristics and the random distribution of counterfeit products to the consumer types affect the effectiveness of a counter strategy. This paper aims to generate insights on how to leverage digital technology to curb counterfeit entities with consideration of consumer characteristics and the random distribution of counterfeits to them.

The authors used game theory and vertical differentiation model to understand and encounter deceptive counterfeiting of brand products. The study understands the economic relationship between a brand product manufacturer and consumer types based on their awareness. Further, the authors have considered different cases in the model to gain useful insights.

The results reveal that when the consumers are proactive, informed and value-conscious brand product manufacturers take digital technology counterstrategy to earn the maximum revenue. Hence, this analysis highlights that the effectiveness of a counterstrategy critically depends on the consumer characteristics, whether they are proactive, informed or unaware.

The study outlines that brand product manufacturers must emphasize on the digital supply chain, product redesign and product tracking facility to empower informed and value-conscious and proactive consumers. Moreover, the government should take steps to create awareness among uninformed consumers via information campaigns.

This paper incorporates the role of consumers and brand product manufacturers to understand and address the deceptive counterfeiting issue.