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In recent years, people have started to realize the importance of environmental protection, and in particular the problem of global warming. Consequently, many governments have started to view decreasing carbon emissions as a priority. Green transportation is one of the policies that is relevant to these efforts. This research aims to optimize the routing plan with minimizing fuel consumption.

In this research, a model is proposed for calculating the total fuel consumption when given a routing plan. Three factors which greatly affect fuel consumption of transportation – transportation distance, transportation speed and loading weight – are taken into consideration. Then a simple Tabu Search is used to optimize the routing plan and an experimental evaluation of the proposed method is performed.

It is shown that the proposed method provides substantial improvements over a method based on minimizing transportation distances.

The experimental results show that the routing plans found by the proposed method require less fuel consumption than that found by optimizing methods in which the distance travelled was minimized. That means that, if the distribution center can transport goods using vehicles with better fuel consumption, and the drivers can drive in the such a way as to reduce the discharge of carbon, then the proposed method can be a strategy for the continuous improvement of fuel consumption.

High-quality cold-chain logistics are key to effectively managing the quality of temperature-sensitive foods. Hence, this study investigates the service quality of such logistics, using a real-life case of temperature-sensitive milk delivery.

This study focuses on developing business analytics for quality control in cold-chain perishable-food logistics, grounded in normal accident theory and stakeholder theory, and tests them using real-world data.

The empirical business-analytics results indicate that cargo locations, logistics status and delivery times are the essential factors that influence the quality of temperature-sensitive milk.

This study confirms that a combination of normal accident theory and stakeholder theory can be usefully applied to the development of strategies for managing perishable-food logistics. As such, its proposed business analytics provide a fresh foundation for research on logistics quality management.

The balance between efficiency and service quality in a logistics system should be assessed carefully, and logistics companies should collaborate with their stakeholders and can help to mitigate potential cold-chain risks.

This pioneering analytical study explores the essential quality issues that confront cold chains and demonstrates how to extract vital insights from temperature-sensitive food logistics monitoring data. As such, it represents a noteworthy contribution to the field of logistics quality management.

The attributes of services can be categorised as service quality and service preference. While studies have addressed the importance of service quality, shippers’ service preference and its relationship to perceived value and purchase intentions remain unexplored. Therefore, the purpose of this study is to propose a causal model in the context of short sea shipping services to investigate the influence of purchase intention through the shipper’s service preference and perceived value.

Structural equation modelling is applied to assess the empirical strength of the relationships in the proposed model. The model is validated through empirical testing by taking samples from shippers in Taiwan.

The results show that service attributes, namely, timing related, pricing related, warehousing, sales, door-to-door, information and advertising, positively affect shippers’ service preference. Service preference significantly affects customer perceived value as well as purchase intentions. Moreover, perceived value strongly affects purchase intentions.

Matching between the product offered and the diversified customer need is key to the business operation’s success. This study suggests that carriers should position themselves to both self-competence and market values.

The purpose of this paper is to explore the data connection, spatial distribution characteristics and trends in genealogical information. First, it implements a spatial-temporal visualization of the Hakka genealogical information system that makes these individual family pedigree charts appear as one seamless genealogy to family and researchers seeking connections and family history all over the world. Second, this study applies migration analysis by applying big data technologies to Hakka genealogies to investigate the migration patterns of the Hakka ethnic group in Taiwan between 1954 and 2014. This innovative library service enhances the Hakka genealogical migration analysis using big data.

The platform is designed for the exchange of genealogical data to be used in big data analysis. This study integrates big data and geographic information systems (GIS) to map the population distribution themes. The general procedure included collecting genealogical big data, geographic encoding, gathering the map information, GIS layer integration and migration map production.

The analytical results demonstrate that big data technology is highly appropriate for family migration history analysis, given the increasing volume, velocity and variety of genealogical data. The spatial-temporal visualization of the genealogical research platform can follow family history and migration paths, and dynamically generate roadmaps to simplify the cartographic steps.

Technology that combines big data and GIS is suitable for performing migration analysis based on genealogy. A web-based application for spatial-temporal genealogical information also demonstrates the contribution of innovative library services.

Big data play a dominant role in library services, and in turn, provide an active library service. These findings indicate that big data technology can provide a suitable tool for improving library services.

Online genealogy and family trees are linked with large-volume, growing data sets that are complex and have multiple, autonomous sources. The migration analysis using big data has the potential to help genealogy researchers to construct minority ethnic history.

Although scholars have paid considerable attention to the relationship between technological diversification and firm performance, research on this relationship has produced mixed findings. To reconcile these inconsistent findings, this study, thus, aims to revisit the performance effect of technological diversification by considering two organizational characteristics as crucial moderators, namely, firm size and financial slack.

To test the research hypotheses, the research sample covers manufacturing firms in the 2008 Standard & Poor (S&P) 500 index. Data regarding the characteristics and patent information of the sample firms were obtained from Compustat and the US Patent and Trademark Office. The hypotheses were tested by using hierarchical regression models.

In a sample of 168 S&P 500 manufacturing firms, this study finds that technological diversification has a positive effect on firm performance. The relationship between technological diversification and firm performance is also found to be positively moderated by firm size, financial slack and their configuration.

The findings of this study further suggest that firms should be aware that the effect of technological diversification on performance can be enhanced or hindered in specific contexts.

As multinational firms seek to acquire competitive cost advantages through global sourcing, it is also important for them to develop effective strategies to reduce possible damage of a negative country‐of‐origin (COO) effect. This study aims to examine whether brand image and evaluation mode could alleviate a negative COO effect.

A 2(COO)×2(brand)×2(evaluation mode) experimental design was employed in order to examine whether brand and COO effects on product evaluation vary under different evaluation modes. The data were analyzed by a repeated measure MANOVA.

The results showed that products made in favourable countries were rated higher in joint evaluation mode than in separate evaluation mode. Conversely, products made in unfavourable countries were better evaluated in separate evaluation mode than in joint evaluation mode. The results of the study are not in favour of the notion that a strong brand image could overcome the negative effect of COO.

Conclusions of the study suggest that the COO effect plays an equally important role in consumer product evaluation for both strong and weak brands. Thus, even for a product with strong brand image, the negative consequences of COO stemming from consumersˇ unfavourable attitudes towards the manufacturing country are not likely to be completely eliminated. Moreover, to alleviate the negative impact of unfavourable COO, marketers may want to avoid direct comparison between products made in unfavourable countries with those made in favourable countries, regardless of their brand strength.

When marketing a product made in an unfavourable country, marketers should manage to create a selling environment facilitating a separate evaluation mode. In contrast, marketers should proactively manage to display products from favourable countries along with those from unfavourable countries in order to further enhance quality perceptions.

The results of the study could help marketers employ advantageous merchandizing or advertising strategies to lessen the negative effect of COO.

Limited research has explored the potential marketing strategies to counter the damage associated with delayed recovery. Based on the construal level theory, this study seeks to suggest that customers tend to focus on different aspects of the compensation according to the speed of recovery. Thus, providing an adequate explanation to customers corresponding to expected recovery speed can effectively alleviate customer dissatisfaction with a delayed recovery.

This study examined the proposed hypotheses using a 2 (immediate vs delayed) by 2 (explanation: process-focused vs outcome-focused) experimental design.

The analytical results show that when an immediate recovery is available, an outcome-focused explanation will result in higher post-failure satisfaction than will a process-focused explanation. Conversely, when a delayed recovery is expected, post-failure satisfaction is higher for customers who receive a process-focused explanation than for those who receive an outcome-focused explanation.

This study thus recommends that firms should provide explanations compatible with expected recovery speed to better enhance post-failure satisfaction.

This study contributes to the body of service recovery literature by examining the differential effectiveness of outcome-focused and process-focused explanations under immediate and delayed recovery conditions. The findings provide a guideline that managers can use to formulate suitable explanations to alleviate the detrimental effects of delayed recovery.

Knowledge sharing intention and group identity are the keys to improving library service quality. The purpose of this paper is to integrate work design questionnaire and affective events theory to understand the relationship between task characteristics and knowledge sharing quality in the context of the library.

Data collected from 204 professional librarians in various libraries provide strong support for the proposed research model. A structural equation modelling analysis was performed using LISREL. The adequacy of the measurement model was evaluated on the criteria of reliability, convergent validity and discriminant validity.

The paper shows that sharing intention and group identity have important effects on knowledge quality. Task characteristics, such as work methods, task variety and social feedback, have strong effects on group identity.

The findings imply that only work methods and social feedback have strong effects on knowledge sharing intention.

The motivation to share librarians' knowledge is critical to successful library service. The paper provides evidence that knowledge quality is built through work methods, task variety and social feedback. Implications for theory and practice and suggestions for future research are discussed.

Notwithstanding a significant amount of literature on the technology acceptance model (TAM), past research has overlooked the role consumers' technology readiness (TR) plays in adoption of self‐service technologies (SSTs). This study aims to fill this research gap by developing and testing a model that integrates the role of TR into the TAM.

The study proposes a research framework to suggest the direct and moderating roles of TR in the TAM. Extant research from various research streams is reviewed, resulting in 13 hypotheses. Data collected from customers with SST experiences are examined through structural equation modeling (SEM) and hierarchical moderated regression analysis.

Results indicate that customer TR enhances perceived usefulness, perceived ease of use, attitude toward use, and intention to use. Results also show that TR attenuates the positive relationship between perceived ease of use and attitude toward using SSTs.

This research represents an early attempt to explain the role of TR in the TAM in the context of SSTs. Future research directions are discussed, with emphasis on incorporating customer differences and situational factors to better understand this model in various service settings.

Findings show that TR influences perceived usefulness, perceived ease of use, attitude toward using SSTs, and behavioral intentions. Therefore, to achieve better SST service outcomes firms implementing SSTs should give increased attention to customer TR. Firms should stimulate the use of technological services by strengthening positive TR drivers (the optimism and innovativeness dimensions) to encourage use of technological services and positive attitudes toward technology, while also reducing TR inhibitors (the discomfort and insecurity dimensions) to lower reluctance to use technology.

This study is the first to integrate the role of TR into the TAM in the context of SSTs.

The purpose of this paper is to present the identification method of restriction parameter and deformation parameter for membrane‐type restrictors.

A worktable mounting on the open‐type hydrostatic bearing is utilized to calibrate recess pressures for regulating outlet pressures of restrictors by changing the load and then both restrictor parameters can be identified from the measurements of the inlet pressure, the outlet pressure, and the flow rate of a restrictor by minimizing the difference between measured and identified flow rates. Furthermore, the influences of supply pressure and restrictor designs on both parameters are also studied.

An identification method for single‐action membrane‐type (SAM) restrictors is obtained directly from experimental results. The measurements of inlet pressure, outlet pressure, and flow rate of the restrictor are substituted into the combined equations for minimization of error between measured and identified flow rates to be solved for restriction and deformation parameters. The identified results show that both parameters can be described by polynomial functions of supply pressure. Both polynomials are regressed by curve fitting from identified results.

The paper shows how to calibrate inlet and outlet pressures of restrictors for designing a hydrostatic bearing system by changing supply pressure and load applied on worktable for the measurements of both pressure and the flow rate of restrictor.