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This study proposes a hierarchic segmentation that develops a tree-based classification model and classifies the cases into groups. This allows for the definition of e-commerce user profiles for each of the groups. Additionally, it facilitates the development of actions to improve the adoption of the online channel that is in such high demand in the current pandemic COVID-19 context.

Regarding the created segments, two extreme segments stand out due to their marked differences and high volume. Segment 3 with 23% of the sample is the group with the most predisposition to use the online channel and is characterised by a high level of trust, more habitual use in comparison with other groups and the belief that its use implies high performance, which indicates they believe it to be useful, quick and helpful for more an effective shopping experience. The other extreme is found in segment 7. This group makes up 17.7% of the total and is the most reluctant to use the online channel. These users are characterised by the complete opposite: they have a low level of trust in this channel. However, the effort expectancy is low, i.e. they consider that the adoption of the online channel does not involve many difficulties in its learning and use. Nevertheless, they use it less regularly than the others.

Based on the conclusions reached in this study, in the current pandemic context in which consumer demand for online shopping channels for all types of products is on the rise, it is recommended that companies focus on the following aspects. It is essential to build trust with the user and show them the real benefits of e-commerce, how it would improve their life and why they should use it. Additionally, it is vital that the user perceives it as an easy procedure that does not require a significant learning curve. Other fundamental aspects would be to reduce any uncertainty the user might have about the online shopping process, to make it as easy as possible, and to design a simple, intuitive and user-friendly interface. It is also recommendable to manage data usage efficiently. To do so, the authors recommend asking the user for the least amount of information possible, offering a data protection policy and assuring them that their information will not be misused nor shared with third parties. All of this provides a series of facilities to modify the online shopping habits of users.

As in most of the research, this study presents a series of limitations that should be debated and that could open future lines of investigation. Firstly, regarding the sample used that was limited to two neighbouring countries with similar profiles a priori; it would be necessary to compare their possible cultural differences according to Hofstede's dimensions as well as increase the number of European countries being analysed to reach a more generalised conclusions. Secondly, the variables used are a combination of those derived from the UTAUT2 model and others suggested in the literature as decisive in technology adoption by users, in this sense other theories and variables could be incorporated to complete a more holistic model.

This work contributes in a general way to (1) analysing the intention to use e-commerce platforms from a set of antecedents previously defined by their importance, after a period of economic and social restrictions derived from the pandemic; (2) determination of customer segments from the classification made by the CHAID analysis; (3) characterisation of the previously defined segments through the successive divisions that were proposed in the analysis carried out.

Other fundamental aspects would be to reduce any uncertainty the user might have about the online shopping process to make it as easy as possible, and to design a simple, intuitive, and user-friendly interface. It is also recommended to manage data usage efficiently. To do so, the authors recommend asking the user for the least amount of information possible, offering a data protection policy, and assuring them that their information will not be misused or shared with third parties.

The results obtained have allowed us to establish predictive and explanatory models of the behaviour of the segments and profiles created, which will help companies to improve their relationships with online customers in the coming years.

本研究擬提出一個會發展基於樹的分類模型、以及會把案例歸入不同的類別的層次細分。這讓我們能為每個類別考慮到電子商務用戶輪廓的定義和解釋；這亦促進我們優化採用在線渠道的發展工作,而在線渠道於現時2019冠狀病毒病肆虐的情況下,實在供不應求。

就創設的細分而言,兩個極端的細分因其明顯的差別和大批量而顯得突出。佔樣本百分之二十三的細分3是擁有最大使用在線渠道傾向的細分,而細分3的特徵包括他們對在線渠道呈高信任度,比其他類別更習慣地使用,以及其相信使用在線渠道會帶來更高的績效,這表示他們相信使用在線渠道是有效的,是快捷的,是可幫助帶來成功的購物體驗的。另外的極端在細分7內發現。這類別佔整體的百分之十七點七,而他們是最不願意使用在線渠道的類別。這類別的特徵和前述的剛剛相反：他們對在線渠道的信任程度是低的,唯其努力期望是低的,也就是說,他們認為使用在線渠道是不會涉及很多在學習上或在實際應用上的困難。即使是這樣,他們較其他人卻較少使用在線渠道。

基於研究的結論,我們的建議是：於目前大流行肆虐期間,消費者對於以在線渠道網購各類商品的需求不斷增加,企業應聚焦以下的範疇：企業必須建立消費者對電子商務的信心,並為他們展示電子商務的真正好處；企業也必須使消費者明瞭電子商務如何能改善其生活,以及他們為何要使用電子商務。更重要的是使消費者覺得使用電子商務是輕而易舉的,又不涉及陡峭的學習曲線。凡此種種,就成為消費者改變其網上購物習慣的動力和誘因。至於其他基本的考慮,包括減輕消費者對使用電子商務的不確定情緒,使電子商務易於使用,以及設計一個簡易的、憑直覺能知曉的、方便使用的介面。另外,值得推薦的是、數據使用情況須有效地管理。為此,我們建議應儘量向使用者索取最低限度的資料,為他們提供資料保護政策,保證他們的資料不會被濫用或與第三者分享。

與其他大多數的研究一樣,本研究展現了一系列值得辯論的局限,而這些局限或許會開展未來研究的領域。首先,考慮到使用了一個局限於兩個以因及果演繹而成的、概況相似的相鄰國家為樣本,我們或許需要根據霍夫斯泰德文化維度理論對這兩個國家進行比較,以瞭解它們的文化差異；另外,為求能達致可普遍適用的結論,我們也需把被分析的歐洲國家的數目增加。其次,被使用的變數是兩組變數的組合,他們是從UTAUT2模型中取得的變數,以及在有關的文獻裡,就技術採用而言、使用者認為是重要的變數。就此而言,若其他的理論和變數能被包含其中,則達致的模型將會是一個更為整體的模型。

本研究就一般而言有以下的貢獻：(一) 、 在因大流行病而引起的經濟和社會限制實施時期後,研究人員分析人們如何從一套過去被認定是電子商務平台的重要前身而選擇使用電子商務平台,本研究對這方面的分析作出了貢獻；(二) 、本研究幫助確定從透過CHAID分析而來的分類中得到的顧客細分；(三) 、本研究透過進行連續分解、幫助歸納過去被認定的細分的特徵。

企業必須建立消費者對電子商務的信心,並為他們展示電子商務的真正好處；企業也必須使消費者明瞭電子商務如何能改善其生活,以及他們為何要使用電子商務。更重要的是使消費者覺得使用電子商務是輕而易舉的,又不涉及陡峭的學習曲線。凡此種種,就成為消費者改變其網上購物習慣的動力和誘因。至於其他基本的考慮,包括減輕消費者對使用電子商務的不確定情緒,使電子商務易於使用,以及設計一個簡易的、憑直覺能知曉的、方便使用的介面。另外,值得推薦的是、數據使用情況須有效地管理。為此,我們建議應儘量向使用者索取最低限度的資料,為他們提供資料保護政策,保證他們的資料不會被濫用或與第三者分享。

本研究所得的結果,讓我們可以建立多個模型、以預測並解說有關的市場部分的行為和被創建的消費者簡介,這會幫助企業改善它們今後與網上顧客的關係。

In this chapter, we discuss talent development in the context of higher education. After discussing the advantages and disadvantages of inclusive and exclusive approaches to talent development, we present empirical data that detail how the participants of a focus group study perceive talent development in higher education. Our data show the importance of a contextualized reading of talent development as the competitive context in academia hinders an inclusive focus on talent development. This context results in a performance-centred, instead of a development-centred approach to talent management, where outperforming others in narrowly defined areas (e.g. publication record) is the main goal. We show that in such a context the development of competitive talent is rewarded, and the development of communal talent is not. The focus on performance instead of (inclusive) development becomes more pronounced when employees move through their career and is believed to have several negative consequences. Mostly women perceived that such a non-inclusive approach to talent development hinders the development and deployment of their talents and obstructs their career progression.

The purpose of this paper is as follows: First, understanding the nature of the relationship between corporate adoption of the concept of societal responsibility [availability of environmental awareness, clear vision of the impact of societal responsibility on financial performance, managers informing employees of the latest developments in societal responsibility programs, managers' response to their corporate social responsibility (CSR) proposals] in the form of an annual report that supports the success of the company's objectives, the company's management encourages employees to participate collectively in societal responsibility programs and to protect the environment from pollution in the petrochemical industry. Second, understand the nature of the relationship between the dimensions of corporate social responsibility concept (cultural, social, economic, ethical and legal) and protect the environment from pollution in the petrochemical industry. Third, the research also seeks to show the role of societal responsibility and its application in the petrochemical companies to protect the environment from pollution in The Governorate of Alexandria – Egypt, and come out with results and recommendations that could help protect the environment from the forms of environmental pollution resulting from the production processes of this industry.

The researcher has relied on each of the following approaches: Case study methodology is a research strategy aimed at solving a problem or facing a particular situation. It is based on preliminary hypotheses through full analysis of all data collected and recorded. Which depends on the study of a limited number of cases or vocabulary in-depth comprehensive study through the study of all or a large number of variables overlapping and interrelated and influential on the problem under consideration. Thus, it provides a deep and rich understanding of what is going on around the research and the processes that are related to it, and not only the external or apparent description of the situation or phenomenon; it cares about the total description and looks at the particles, in relation to the whole. Quantitative approach: by giving a numerical description indicating the size or size of the phenomenon or the degree of association with the phenomenon. Other phenomena. Accordingly, the role of the petrochemical companies in Alexandria Governorate, and the social responsibility programs carried out within the governorate in terms of importance, growth and requirements, and the most important characteristics and constraints and components and methods of work and developments have been described. Thus, the researcher can analyze the relationship between CSR and environmental protection from pollution in Alexandria Governorate.

There is paucity in the studies that dealt with the relationship between CSR and environmental protection against pollution in public organizations. There is agreement among the sample on the importance and feasibility of adopting the concept of social responsibility and placing it at the top of the top management concerns, especially in the field of petrochemical companies. With the need to take concrete implementation measures to support social responsibility programs aimed at serving the community among all stakeholders. The effective implementation of the mechanisms for the implementation of meaningful social responsibility programs requires fundamental changes in management practices, existing organizational structures and the quality of personnel working in the relevant departments, in general, and the social responsibility group, in particular, which may be difficult for political and economic reasons.

Time: The study period was set from 2015 to 2017. Place: The study focuses on the petrochemical companies operating in Alexandria. Humanity: The study focuses on the employees of the petrochemical companies operating in Alexandria Governorate.

The adoption of social responsibility positively affects the protection of the environment from pollution, and this effect shows that the adoption of the concept of corporate social responsibility is influenced by the following factors: increasing the participation of workers with healthy environmental contributions to the productive process; increasing the companies' economic and social activities toward protecting the environment from pollution; increasing the capacity of companies to pay greater costs to preserve the environment; increasing the awareness of green consumers with the products it offers Companies; development of continuous internal work environment companies; and clearly defined strategy followed in social responsibility programs.

The social responsibility of the public organizations derives their strength through, first, the keenness of these organizations to analyze the variables of the ethical dimension of social responsibility and their availability, which will lead the organizations to provide their services with the highest quality and sincerity. That this analysis (ethics of individuals) as training members of the social responsibility team to solve problems using brainstorming and provide employees with official data related to improving work (ethics of leadership), such as the identification of business objectives through the participation of managers with subordinates, and the punishment of workers who exhibit immoral behaviors (ethics of productive processes) as a decision-making process to ethical standards regardless of the costs involved. When there is an immoral behavior and managers are responsible for implementing the changes needed to reach the targeted outcomes), second, promote partnerships with other relevant sectors for community service.

According to the results of the previous studies and the applied study results, the researcher would like to submit a mechanism to the directors and heads of the boards of directors of the Egyptian petrochemical companies under study.

The food industry is continuously developing its online services called food delivery applications (FDAs). This study aims to evaluate FDA's importance–performance and identify strategies to maximize its potential gains from a business partner's perspective.

Data are collected from 208 FDA partners in Indonesia. Importance–performance analysis (IPA) is applied to evaluate the FDA feature and extended the theory of potential gain in customer value (PGCV) to achieve potential gains from FDA business partners.

This study provides a clear and measurable direction for future research to develop FDA performance. Owning customer data, revenue sharing and competitive advantage are the most potential gains from joining the FDA from the business partner perspective.

The respondents are restaurants from the micro, small, and medium enterprises levels. Further research should involve middle to upper level restaurants to discover all business partners' perceptions. This will be very helpful for FDA providers interested in improving the best performance for all their partners.

FDA providers must focus on improving and maintaining the features of owning customer data, revenue sharing, competitive advantage, stable terms and conditions, customer interface, building customer loyalty, online presence, user credit rating, promotion and offers, delivery service and sales enhancement to increase consumer satisfaction and meet the expectations desired by business partners.

This research provides a meaningful theoretical foundation for future work. It extends the theory of PGCV using the value of a partner perspective as a substitute for customer value; hence, the authors call it a potential gain in partner value.

Supplier segmentation provides companies with suitable policies to control each segment, thereby saving time and resources. Sustainability has become a mandatory requirement in competitive business environments. This study aims to develop a clustering-based approach to sustainable supplier segmentation.

The characteristics of the suppliers and the aspects of the purchased items were considered simultaneously. The weights of the sub-criteria were determined using the best-worst method. Then, the K-means clustering algorithm was applied to all company suppliers based on four criteria. The proposed model is applied to a real case study to test the performance of the proposed approach.

The results prove that supplier segmentation is more efficient when using clustering algorithms, and the best criteria are selected for sustainable supplier segmentation and managing supplier relationships.

This study integrates sustainability considerations into the supplier segmentation problem using a hybrid approach. The proposed sustainable supplier segmentation is a practical tool that eliminates complexity and presents the possibility of convenient execution. The proposed method helps business owners to elevate their sustainable insights.

With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with essential knowledge acquisition (KA) facilitating the journey toward hybrid work agility (HWA). This study, thus, aims to explore the impact of KOL and KA on HWA and reveal whether this effect stems uniformly from a single homogenous population or if there is unobserved heterogeneity leading to identifiable segments of agile KWs.

Data was collected through stratified sampling from 416 employees from 20 information technology enabled services companies involved in knowledge-intensive tasks. Partial least squares (PLS) structural equation modeling approach, using SMART PLS 4.0, has been applied to examine the effect of KOL and KA on HWA. Finite mixture PLS, PLS prediction-oriented segmentation and multigroup analysis have been used to identify segments, test segment-specific path models and analyze the significance of the differences in the path coefficients for unobserved heterogeneity. Predictive relevance of the model has been determined using PLS Predict.

Results indicate that KOL contributes to employees’ KA and HWA. A significant positive relationship is also reported between KA and HWA. The model has medium predictive relevance. A two-segment solution has been delineated, wherein independent agile KWs (who value autonomy and personal agency over leadership for KA) and dependent agile KWs (who depend on leaders for relational and structural support for KA) have been identified. Thus, KOL and KA play a differential role in determining HWA.

The authors’ major contribution to the knowledge body constitutes the determination of antecedents of HWA and a typology of agile KWs. Future researchers may conduct segment-wise qualitative analysis to delineate other variables that contribute to HWA.

Technological advances necessitate that knowledge-intensive industries foster agility in employees for strategic agility of the organization. For effecting agile adaption of an organization to the knowledge economy conditions, it is pertinent that the full potential of this human resource be used. By profiling HWA of KWs on the basis of dimensions of KOL and the level of their KA, organizations will be able to help employees adapt better to rapidly changing work conditions.

HWA is a novel concept and very germane in a hybrid working environment. To the best of the authors’ knowledge, this is the first study to examine the effects of the dimensions of KOL and KA in relation to HWA, along with an empirical examination of unobserved heterogeneity in the aforementioned relationship.

In order to better optimize the internal management system of book publishing and to cope with the changes in the external market environment, the purpose of this paper is to carry out cross-border publishing with the help of a transmedia storytelling model to realize the transformation and upgrading of the industry. Focusing on the relationship between the book publishing transmedia storytelling model and business performance, the moderating effect of the innovation environment on different variables is assessed.

This paper proposes several feasible hypotheses based on existing research. The research data came from 365 managers of Chinese book publishing organizations, and the scale was validated by Cronbach’s a, composite reliability (CR) and average variance extracted (AVE). Reliability and validity were verified, and correlation and regression analyses were used to test the impact of the book publishing transmedia storytelling model on business performance and to analyze the moderating role of the innovation environment.

The results show that the book publishing transmedia storytelling model (content production, technology integration, organizational innovation, marketing integration) helps to improve business performance (market performance, financial performance), and the innovation environment has a positive moderating effect on the relationship between the book publishing transmedia storytelling model and business performance, which provides a guarantee for the transformation and upgrading of book publishing. The market information reflected in the innovation environment has a certain role in promoting the innovation and business performance of the book publishing transmedia storytelling model.

The empirical evidence provides a theoretical link between the book publishing transmedia storytelling model and business performance, but there are still some shortcomings, and more factors, such as equity structure, government subsidies and research and development investment, should be included in future research. In addition, the scope of the research should be broadened on this basis to make the results of the data analysis more objective.

This paper introduces the transmedia storytelling model and deeply analyzes the relationship between the book publishing transmedia storytelling model and business performance, which is of great practical significance for optimizing the application and service quality of book publishing, prolonging the industrial chain, enhancing the interaction and participation of users and perfecting the business management system of the book publishing industry.

The application and research of the book publishing transmedia storytelling model are imperfect. Therefore, this paper not only helps to promote the innovation of book publishing organizational structure and improve the management system of business performance, but also may help to improve the innovation environment of book publishing enterprises and promote the diversification of industrial structure.

This study aims to analyse how multinational corporations (MNCs) organise value chain activities to penetrate new market segments. It contributes by expanding traditional decisions regarding the vertical fine-slicing of value chain activities (whether performed internally or externally) and the consideration of resource-sharing decisions (integration or separation) for each value chain function.

The authors draw on primary data collected from two case study firms operating in the large emerging Chinese market: Volvo Construction Equipment AB and Epiroc AB. In-depth cases illustrate how foreign MNCs expand into new market segments and simultaneously target both the lower-priced mid-market and the premium segments in the Chinese mining and construction industry.

The results reveal that product diversification creates challenges for managers who must oversee new (vertical) value chains, often simultaneously. Beyond geography and modes of governance, managers must decide whether to integrate or separate value chain activities for the new product lines. The study identifies four main strategic choices for firms to address this complexity, focusing on the decision to internalise or externalise (i.e. within or across organisational boundaries) and integrate or separate value chain activities between different product lines.

This study builds upon the internalisation theory and recent international business contributions that focus on value chain configurations to explain MNCs’ product diversification as a growth strategy in a host emerging market. It also sheds light on the choice of conducting new activities in-house or externally and elucidates firms’ managerial decisions to operationally integrate or separate individual value chain activities. The study provides insights into the drivers explaining managerial decisions to configure value chain activities across product lines and contributes to the growing body of literature on MNC activities in emerging economies by highlighting that product diversification impacts entry mode diversity and resource sharing across units.

Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.

The purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.

Using individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).

The results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.

Substantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.