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The purpose of the study is to quickly identify significant heterogeneity of surrounding rock of tunnel face that generally occurs during the construction of large-section rock tunnels of high-speed railways.

Relying on the support vector machine (SVM)-based classification model, the nominal classification of blastholes and nominal zoning and classification terms were used to demonstrate the heterogeneity identification method for the surrounding rock of tunnel face, and the identification calculation was carried out for the five test tunnels. Then, the suggestions for local optimization of the support structures of large-section rock tunnels were put forward.

The results show that compared with the two classification models based on neural networks, the SVM-based classification model has a higher classification accuracy when the sample size is small, and the average accuracy can reach 87.9%. After the samples are replaced, the SVM-based classification model can still reach the same accuracy, whose generalization ability is stronger.

By applying the identification method described in this paper, the significant heterogeneity characteristics of the surrounding rock in the process of two times of blasting were identified, and the identification results are basically consistent with the actual situation of the tunnel face at the end of blasting, and can provide a basis for local optimization of support parameters.

The purpose of this paper is to develop a quantitative risk assessment method for agricultural products cold chain logistics to assess the condition of the fresh agricultural products cold chain process objectively and accurately.

A risk assessment index system of agricultural products cold chain logistics is designed on the basis of the risk identification for the process of agricultural products cold chain logistics. This paper first uses catastrophe progression method and a new maximum deviation method to build an improved catastrophe progression assessment model for agricultural products cold chain logistics. In order to verify the reliability and validity of the model, two representative enterprises are selected as the case in the study.

The results in the empirical research indicate strong support for the assessment model and coincide with the reality. The risk assessment index system can also reflect the key risk factors from agricultural products cold chain logistics scientifically. In addition, the improved catastrophe progression assessment method proposed in this paper can be scientific and reasonable to predict risk.

This paper contributes to provide a new risk assessment model for agricultural products cold chain logistics. The new model overcomes the limitation of subjective empowerment and it increases the objectivity and scientificity in the process of cold chain logistics risk assessment. This paper also shows that practitioners involved in the field of products cold chain logistics can manage the potential risk by a set of scientific methods for assessing the risk before the accident.

The paper provides a practical guideline to practitioners, especially for cold chain logistics managers, relevant management departments, and cold chain logistics management consultants. It is proved that the new risk assessment method and the risk assessment index system of agricultural products cold chain logistics can help them assess the risk scientifically and reasonably.

Although the calculation is simple, the new model can overcome the limitation of subjective empowerment scientifically and reasonably, and thus has important practical value.

This study analyzes how digital technologies collaboration, and technological capabilities affect tourism products' advantage and supply chain resilience via virtual integration and customer service capabilities.

To achieve the goals of this study, a digital transformation model was formulated based on the real option theory (ROT) and digital competencies perspective. Data were collected from travel agencies in Taiwan. This study uses the partial least square structural equation modeling (PLS-SEM) technique to analyze the research model, and 384 samples were collected from travel agencies for analysis.

The research results point out that digital technology collaboration and technical capabilities affect virtual integration and customer service capabilities; customer service capabilities should also be regarded as key influencing variables to improve tourism product advantages and supply chain flexibility.

This study shares a unique perspective on the digital transformation model, which includes antecedents, mediators and moderators, to construct the critical effects for analyzing the tourism products' advantage and supply chain resilience.

Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

While the three lines model (TLM) provides an organizational structure to execute risk and control duties, research and practice show limitations in the model's implementation. These limitations result in governance issues. Such issues, together with control weaknesses, could be addressed by leveraging properties of distribution, transparency, and immutability of blockchain technology. To this end, in this paper the authors propose a conceptual control framework based on blockchain technology to augment control practice.

The design of the resulting blockchain-based control framework (BBCF) and its prototype, based on the design science research methodology (DSRM), is presented and discussed in terms of the potential impact in the context of the identified problems within the TLM.

One potential outcome of BBCF could be to redefine the scope and boundaries of some of the activities in audit and control practices from a more static to a more dynamic and prospective role. In a larger context of improving governance practices, the BBCF could set the path for a more inclusive and participatory interaction between the different governance actors of an organization.

However, this assumes that blockchain is more widely adopted despite its complexity and rigidity.

BBCF covering both a conceptual model design and a reference implementation provides an innovation in audit and control. BBCF could include all relevant stakeholders who have an interest in corporate governance and control activities, including the regulators.

The contribution intends to serve both as a starting point for discussing the evolution of audit and control practice based on blockchain technology, as well as an initial actionable prototype for experimentation and further development.

The paper aims to address the organizational transformation of firms for value creation resulting from cloud computing (CC).

With reference to the theory of organizational fit, we modeled organizational transformation as a function of five aspects of CC practice: functionality, data management, roles and competences of information technology services, control and organizational culture. The output variable was tested against a set of input variables defined with reference to the technology–organization–environment (TOE) and technology acceptance model (TAM). Based on a sample of 487 companies in seven countries in Europe, Asia, and the United States, the authors distinguished two groups of firms: transformational and hyper transformational.

The results highlight the key factors that determine whether a firm falls into one of these two groups, and include perceived usefulness and perceived ease of use, complexity and compatibility of CC technology, and adequacy of resources. Top management support and government policy are found to only play a role for the transformational group while, surprisingly, vendor support had no impact for either group.

This research contributes to the literature on the role of digital transformation in value creation and on digitization of firms and organizational design, notably by considering the contribution of CC to the organizational dimension. To the best of the authors’ knowledge, this is the first study to make the link between TOE and TAM models and organizational fit theory, thereby going beyond the general approach to adoption found in information system research.

The purpose of this paper is to examine, in a global perspective, the oil, gold, US dollar and stock prices interdependencies and to identify instantaneously direct and indirect linkages among them.

A methodology based on simultaneous equations system was used to identify direct and indirect linkages for the period 1995-2015. The authors try initially to find theoretical answers to main question of the study by discussing causal bilateral relationships while focusing on multilateral interactions.

The results show significant interactions between all markets. The authors found a negative relation between oil and stock prices but oil price is significantly and positively affected by gold and USD. Oil price is also affected by oil futures prices and by Chinese oil gross imports. Gold rate is concerned by changes in oil, USD and stock markets. The US dollar is negatively affected by stock market and significantly by oil and gold price. Indirect effects always exist which confirm the presence of global interdependencies and involve the financialization process of commodity markets.

Motivation of this research paper is the substantial implications of price movements on real economy and financial markets. Understanding that co-movement has great value for investors, policy makers and portfolio managers. This paper differs from previous studies in several aspects. First, most of the research papers focus on bilateral linkages solely, while the authors’ investigation was implemented on all the four markets simultaneously. Second, the study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

The purpose of this paper is to explore how business-to-business (B2B), intercultural, interpersonal salesperson–customer relationships develop using the lens of identity management theory (IMT; Imahori and Cupach, 2005).

The research uses qualitative semi-structured interviews on 18 targeted relationships with customers from another culture conducted with business-to-business salespeople.

The findings indicate that our respondents' relationships moved from trial toward enmeshment and on occasion toward the renegotiation phase, as described in IMT. In the case of low cultural diversity between salesperson and customer, the relationships reached the trial and enmeshment phase. In the case of high cultural diversity between salesperson and customer, the relationships on occasion evolved toward the renegotiation phase. Salespeople's cultural intelligence (CQ) facilitates the development of interpersonal, intercultural salesperson–customer relationships.

The authors transfer IMT from the personal relationship development arena to B2B intercultural, interpersonal relationships, address a gap in the literature in the understanding of salesperson–customer interpersonal relationships in different contexts and develop a theoretical model to understand intercultural, interpersonal salesperson–customer relationship development across different levels of cultural diversity.

This study investigates how asset specificity, relational governance and firm adaptability relate with supply chain integration (SCI), considering selected food processing firms (FPFs) in Uganda.

This study applies a quantitative research methodology. This research draws on a sample of 103 FPFs that have been selected from a population of 345 FPFs located in Kampala district. Hypothesis testing was done using Smart PLS version 3.

Asset specificity has a significant positive relationship with SCI, and firm adaptability partially mediates this relationship. Also, there is a full mediation impact of firm adaptability on the relationship between relational governance and SCI.

This study focused on perceptual measures to get responses from managers on the level of integration with key suppliers and customers, yet firms deal with a number of suppliers and customers.

This study contributes to existing literature on SCI by applying the transaction cost theory. The study focuses on the influence of asset specificity, relational governance and firm adaptability on SCI in the food processing sector. Literature on relational governance in supply chain using the transaction cost theory remains scanty. Few studies have also focused on firm adaptability as a mediator in the FPS with specific focus on Uganda, yet the sector is highly faced with uncertain events. The uncertain events in the sector and in developing countries call for adaptive strategies. Additionally, this study is the first to use firm adaptability to mediate the influence of asset specificity and relational governance on SCI more so in a developing country like Uganda where the FPS is one of the most important in the economy.

Since the onset of the COVID-19 pandemic in China, student engagement in online learning has been a critical issue for all educational institutions. The university student engagement inventory (USEI) is the most used scale for assessing the construct of student engagement. The present study aimed to evaluate the psychometric properties of the USEI among 1504 Chinese university students who completed a survey through an online platform between December 2020 and January 2021.

In this cross-sectional study, content validity, construct validity and reliability of the scale were assessed.

The results supported the three-factor model with acceptable goodness of fit (χ² (71) = 369.717, p = 0.13, χ²/df = 5.207, comparative fit index (CFI) = 0.967, normed fit index (NFI) = 0.960, Tucker–Lewis index (TLI) = 0.958, standardized root mean square residual (SRMR) = 0.030, root mean square error of approximation (RMSEA) (90% CI) = 0.053 [0.049, 0.057]), good internal consistency and construct reliability (Cronbach's alpha and omega coefficient >0.70) and strong convergent validity. Also, the measurement invariance was confirmed across gender.

This study showed that the 3-factor structure of USEI with Chinese university students had good construct validity, internal consistency and reliability. It could help measure student engagement in online learning in China.