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The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road.

A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain.

The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain.

Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis.

This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.

This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.

First, taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion, the critical buried depth of the large section tunnel was determined. Then, the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios, and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality (BQ) index of the rock for different rock classes. Finally, the influences of thickness-span ratio, groundwater, initial stress of rock and structural attitude factors were considered to obtain the corrected BQ, based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed. This evaluation method was then applied to Liuyuan Tunnel and Cimushan No. 2 Tunnel of Chongqing Urban Expressway for verification.

This study shows that under different rock classes, the tunnel safety factor is a strict power function of the thickness-span ratio, while a linear function of the BQ to some extent. It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.

The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability. The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.

The influence of road surface temperature (RST) on vehicles is becoming more and more obvious. Accurate predication of RST is distinctly meaningful. At present, however, the prediction accuracy of RST is not satisfied with physical methods or statistical learning methods. To find an effective prediction method, this paper selects five representative algorithms to predict the road surface temperature separately.

Multiple linear regressions, least absolute shrinkage and selection operator, random forest and gradient boosting regression tree (GBRT) and neural network are chosen to be representative predictors.

The experimental results show that for temperature data set of this experiment, the prediction effect of GBRT in the ensemble algorithm is the best compared with the other four algorithms.

This paper compares different kinds of machine learning algorithms, observes the road surface temperature data from different angles, and finds the most suitable prediction method.

The authors propose a dairy bundle, integrating strategies to jointly maximise producer revenue and consumer utility according to the latter's preferences.

An algorithm based on a nested logit model identifies the bundle maximising producer revenue based on factors affecting consumer purchase behaviour. The data are drawn from a mall-intercept survey administered in Iran, with consumers stating a hypothetical choice among a comprehensive set of dairy products.

Demographic characteristics and marketing mix elements significantly affect consumers' preferences. An algorithm based on the estimated dissimilarity parameter determines the best bundle of dairy products, simultaneously obtaining the highest utility and the highest expected revenue.

Consumer preference and maximum producer or retail seller income are considered simultaneously. The bundling promotion strategy is widely used for food offerings and fresh foods and can be extended to other products.

我們擬根據消費者偏好，提出一個整合了多個策略的捆綁包，以使生產製作者得到最高的收入和最佳的消費者效用。

研究人員根據巢式Logit 模型的演算法確認了一個捆綁包，以使生產製作者能得到最高的收入，而這均建基於會影響消費者購買行為的各個因素。有關的數據取自於伊朗的商場內進行的攔截調查，而回應的消費者須假想他們從一整套乳製品中選擇他們會購買的產品。

研究結果顯示，人口特徵和市場營銷組合元素均會顯著地影響消費者的偏好，一個基於估算的相異性參數而建立的演算法可確認最佳的乳製品捆綁包，這演算法同時也可取得最佳的裨益和最高的預期收入。

於本研究中，研究人員同時考慮消費者的偏好和生產製作者或零售賣家的最高收入。捆綁式的促銷策略在食物供品和新鮮食品方面被廣泛使用，這策略可擴展至其他產品。

乳製品捆綁包、消費者偏好、最佳化演算法、巢式Logit 模型.

This paper aims to deepen understanding of the role played by new technological tools used in customer–travel agency (TA) interactions by analysing the TA owner/managers' perceptions, pre- and post-Covid-19, regarding the effectiveness of in-store traditional and innovative tools.

This exploratory study is based on a questionnaire-based survey conducted among Italian TAs and distributed via email from September 2020 to January 2021.

The study highlights how, even among TAs, the role of in-store technology is gradually taking on greater importance, and it delves into the specific business and socio-demographic factors that seem to cause differences among agencies.

The study focuses on the Italian context, which does not allow for any generalisations. Furthermore, it is only the travel agent perspective that is observed and not the consumer's.

In addition to helping to bridge the literature gap, this study on in-store technologies focuses on the TAs sector, where human resources and human relationships play a decisive role in customer experience and interaction. The paper investigates the travel agents' point of view regarding the introduction of new in-store technologies; it also highlights their growing adoption and use, overall, despite the travel catalogue still remaining the main tool for interacting with customers. The study also shows how the advent of Covid-19 has increased travel agents' propensity to use digital technologies.

This study aims to analyze the development direction of train speed, density and weight in China.

The development of China's railway in the past 40 years can be divided into 3 stages. At the stage of potential tapping and capacity expansion, it is important to improve the train weight and density by upgrading the existing lines, and improving transportation capacity rapidly. At the stage of railway speed increase, the first priority is to increase train speed, reduce the travel time of passenger train, and synchronously take into account the increase of train density and weight. At the stage of developing high-speed railway, train speed, density and weight are co-developing on demand.

The train speed of high-speed railway will be 400 km h⁻¹, the interval time of train tracking will be 3 min, and the traffic density will be more than 190 pairs per day. The running speed of high-speed freight EMU will reach 200 km h⁻¹ and above. The maximum speed of passenger train on mixed passenger and freight railway can reach 200 km h⁻¹. The minimum interval time of train tracking can be compressed to 5 min. The freight train weight of 850 m series arrival-departure track railway can be increased to 4,500–5,000 t and that of 1,050 m series to 5,500–6,400 t. EMU trains should gradually replace ordinary passenger trains to improve the quality of railway passenger service. Small formation trains will operate more in intercity railway, suburban railway and short-distance passenger transportation.

The research can provide new connotations and requirements of railway train speed, density and weight in the new railway stage.

Consumers' willingness to pay premium (WTPP) for two different types of agricultural brand labels (enterprise and regional), are evaluated through a non-hypothetical Random n-price auction experiment during the online purchase of fresh agricultural products. The purpose of this paper is to evaluate the two WTPP, compare their differences, and explore their sustainability.

Data were collected in July–August 2020 from a sample of 310 consumers in Liaoning Province, China. A nonhypothetical random n-price auction experiment was implemented in a simulated online shopping environment.

The results show that WTPP exists, and WTPP level of regional brand labels is higher than that of enterprise brand labels. Consumers' WTPP is sustainable. Consumers with low WTPP for enterprise brand labels and consumers with high WTPP for regional brand labels have stronger willingness to repurchase.

The results have direct practical implications for developing brand agriculture and encouraging “brand consumption”. The results can provide theoretical reference for policymakers, enlightenment for the development and effective dissemination of agricultural brand labels and important information to e-retailers on how to sale agricultural products with agricultural brand labels.

To the best of the authors' knowledge, no previous study has related WTPP and its sustainability for agricultural brand labels in China. We try to fill a gap in literature on consumers' WTPP for agricultural brand labels. And the authors explore the sustainability of WTPP by analyzing the impact of WTPP on repurchase intention and recommendation intention respectively.

The purpose of the paper is to present an empirical study that examines the impact of digitalization on informative, strategic and operational marketing activities in manufacturing companies from the entrepreneurial perspective.

A research project was carried out in 205 Italian manufacturing companies by using the questionnaire method. An exploratory research study was conducted with hierarchical cluster analysis.

The analysis shows the existence of seven clusters of manufacturing companies that differ by the impact of digitalization on marketing activities from the entrepreneurial perspective. Two clusters have a high positive impact of digitalization, primarily on informative and strategic marketing activities. Two clusters are characterized by a low positive impact of digitalization and three clusters perform an intermediate level of digitalization. Furthermore, these groups of clusters differ in terms of the influence of digitalization on customer value.

The small size of the sample and the geographic origin of the companies imply limited generalizability; further research on the topic is thus recommended.

The study suggests that companies should digitalize many key marketing activities to increase marketing effectiveness and customer value. To achieve high levels of digitalization and thus increase their competitiveness, manufacturing companies should consider the importance of relevant technologies and skills.

By focussing on the impact of digitalization on informative, strategic and operational marketing, which has not yet been empirically investigated, the present study reveals many new elements concerning the marketing process in the digital era from the entrepreneur's point of view.

Based on the main studies presented in the literature, this work aims to examine the level of student satisfaction towards the on-campus accommodation service provided by an Italian university. Notably, the objectives of the study are twofold: (1) to examine the mediating role of student satisfaction on the relationship between university on-campus accommodation service quality and word-of-mouth and (2) to determine whether there is any significant difference in students' satisfaction towards on-campus accommodation in terms of gender and the halls of residence.

The study is based on the results of a survey carried out through an online questionnaire by 381 students living on campus at the University of Urbino.

The findings revealed that the quality perceived by university students in relation to individual services had a positive impact on their general satisfaction towards the halls of residence experience.

The study presents some limitations such as lack of temporal comparisons, a focus on specific service quality items and the fact that it refers to a single Italian university.

The findings of this study will help the management of public universities to improve the quality of services in their halls of residence for the satisfaction of their students.

To the authors' knowledge, there have been no previous studies about on-campus accommodation service quality conducted in Italy. The study contributes to enrich the service quality literature, confirming both that the sum of the quality of individual elements is not as the overall satisfaction and the outcome intention of positive WOM depends not only on service quality attributes, but also from an overall evaluation of satisfaction.

The effects of big data in this present age are highly significant, and big data have become more applicable to society. Big data technology has been adopted by many, and its applications are utilized at national, organizational, and industry levels. This transformation of industries due to big data is changing working practice in academia, business, the humanitarian sector, and government, as they offer insights and positive effects across all sectors, making legal, economic, political, social, and ethical impacts in our world and producing innovation, efficiency, better decision-making, and a greater return on investments. This paper reviews the social implications, risks, challenges, and present and future opportunities of big data.