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The authors observe the impact of certain aspects of globalization on the work-family interface in India. Specifically, the purpose of this paper is to investigate the impact of life in Tier 1 (more globalized) vs Tier 2 (less globalized) cities, family/work collectivism and gender on work-family conflict (WFC) – both work interfering with family (WIF) conflict as well as family interfering with work (FIW) conflict.

The study surveyed 628 young employees on cultural values of collectivism and WFC.

Results suggest a main effect of tier in which Tier 1 city individuals experience more of both forms of WFC than Tier 2 city individuals. However, two- and three-way interactions between family/work collectivism and tier greatly moderate the main effect. Interactions indicate that family collectivism decreased WIF more for Tier 1 as compared to Tier 2 cities and work collectivism decreased FIW more for Tier 2 as compared to Tier 1 cities. The results suggest that high family collectivism creates high conflict for those who are low on work collectivism and high family collectivism creates low conflict for those who are high on work collectivism.

The paper provides great insight into globalization and WFC within the context of cultural values. The paper calls for further studies on globalization, work life enrichment and cultural values.

The results build a case for more paid and organizationally supported interventions for work-life balance in India.

Large scale institutional changes, such as globalization, call for a reexamination of cultural dynamics. This study heeds the call and examines WFC in the context of rapid economic and social transformation occurring in India by bridging globalization, cultural change and WIF/FIW.

To evolve sustainable practices for human resource planning (HRP) for hospitals being set up in Tier 2/3 cities in India. The purpose of this study is to determine the strategic challenges are faced by hospitals in Tier 2/3 cities. To align HRP/workforce planning to departmental strategic/business planning of the hospital in the defined context. To address the dilemmas of the prospective health-care workforce in Tier 2/3 cities.

The integrated methodology adopted uses the grounded approach for building theory from practice. Due to the lack of research in the identified context, the study relies on a review of literature related to health-care practices, HRP and general management inputs to evolve the exact interview questionnaire. The subsequent empirical analysis is based on interviews of niche human resource experts in private hospitals.

The traditional and successful model of private hospitals in the metro cities cannot be transplanted to the Tier 2/3 cities. The thumb rule on a ratio between the doctors, paramedic staff, nurses and other support staff requires to be modified as necessary. Uncertainty in the new context requires the outlook to be basic, uncomplicated, flexible and agile. Attracting and recruitment strategies require adopting an innovative and multipronged approach. Sourcing high-end specialists need not follow the retainership model of employment.

The need to penetrate health-care services to the Tier 2/3 cities within India cannot be disputed. With the increase in disposable income and standard of living in these cities, access to quality and affordable health care is also imperative. The study is a pioneering effort to suggest a practicable and uncomplicated model for hospital setup in the identified context, with a focus on HRP.

This paper offers novel perspectives to the HRP of health-care personnel for a hospital setup in Tier 2/3 cities in India. For the success of private hospitals and their financial viability, this planning is of utmost importance. There is an attempt to fill the knowledge gap in the context which has been rarely explored or ventured. In addition, the policy initiatives suggested are expected to encourage the growth of private hospitals within the Tier 2/3 cities in India.

The purpose of this paper is to validate the conceptual model that presents the determinants of Tier 2 consumer’s online shopping attitude and the interrelationships among the constructs across the three Tier 2 cities in India.

The paper uses survey-based data from three Tier 2 cities of North India – Kota, Agra and Jalandhar and uses a combination of statistical techniques to assess psychometric properties of the scales and conduct the measurement and structural invariance.

The findings of the paper reveals that technology readiness, consumer innovativeness, fondness for branded products and perceived brand unavailability act as determinants of online shopping attitude and there is a positive relationship between online shopping attitude and online purchase intention among Tier 2 consumers in India while perceived offline hedonic value do not have any significant impact.

Future researchers can use this model with additional confidence given its cross-segment robustness.

Online marketers can use the antecedents identified in this study to develop and encourage positive online shopping attitude in small town India.

This research paper is the first one that investigated online shopping attitudes of Indian Tier 2 consumers. Importantly, it validated the determinants of online shopping attitude among Tier 2 consumers. National and international e-tailers aiming to develop and expand their operations to India now have the critical empirical verification concerned with the determinants of online shopping attitude and behaviour in India which would be meaningful to develop a sound marketing strategy.

Housing prices in China have increased rapidly over the past decade. Motivated by the fact that the real estate market and bank credit scale are vastly different in Chinese cities, the purpose of this paper is to compare the impact of bank credit on house prices in first- and second-tier cities in China.

In this study, a panel data method was used to investigate 19 first-tier cities and 30 second-tier cities between the period 2003 and 2018.

The empirical analysis undertaken in this study found that bank credit was relevant to house prices but varied in different cities in which house prices in second-tier cities tended to be more affected by bank credit compared to those in first-tier cities. In contrast, population was found to be a dominant factor that influenced house prices in first-tier cities. Likewise, the factors, per capita and gross domestic product, were found to exert a significant influence on house prices in first- and second-tier cities.

This paper provided numerous policies to control the price of housing in first- and second-tier cities.

The housing prices, bank credit scale and population distribution are vastly different in different cities in China. This research considers these differences while examining the dominant factors that affect house prices in first- and second-tier cities in China.

Cities remain an understudied unit of analysis for understanding the motives of multinational enterprises’ (MNE) foreign direct investment (FDI), with subnational locations in International Business (IB) research to date predominantly captured via the phenomenon of agglomeration. As regional integration projects, such as the European Union and to a lesser degree NAFTA, increasingly reduce the importance of national institutional environments, this paper argues regional and subnational levels become more important for studying MNE location choice. This paper aims to evaluate the explanatory contribution of regional and subnational levels of analysis to understanding MNE location choice.

A qualitative deductive bottom-up multiple-case study research design is adopted to study the city location choices and FDI motives of six automotive and six commercial banking companies. These purposefully sampled manufacturing and service MNEs have different home countries and regional orientations. Data on their foreign investments across the extended Triad of Europe, North America and Asia-Pacific were collected for the time period of 2000–2021.

Findings suggest that different classes of city tend to attract specific types of FDI and that these patterns might vary across sectors and be influenced by the regional strategic orientations of MNEs. Industry-specific findings reveal the importance of related and support industries and partners in a city location for the automotive MNEs, while the commercial banks seek investment opportunities in cities that allow acquisition targets that have an attractive customer based and will improve their local market knowledge.

The findings provide evidence in support of MNEs in manufacturing and service industries perceiving the attractiveness of three city types in different ways across the Triad regions.

This study aims to examine the evolution of spatial–temporal patterns in China’s hotel industry from 1978 to 2018.

A database comprising over 140,000 hotels with more than 30 rooms was created. The exploratory spatial–temporal data analysis (ESTDA) method, based on space–time cube model, was used to explore and visualize the spatial–temporal pattern of hotels.

The Chinese hotel industry can be divided into two development stages, namely, a large hotel-dominant stage before 2000 and a small–medium-sized hotel-dominant stage after 2000. China’s prefecture-level cities were clustered into four tiers. The higher the tier, the earlier the city will initiate hotel development. The Chinese hotel industry has four continuous hotspots (the Yangtze River Delta, Pearl River Delta, Bohai Rim and Sichuan and Chongqing) and some temporary hotspots.

This study lacks quantitative investigation, which could show the underlying mechanism of the evolution of the Chinese hotel industry.

This study is the first to investigate China’s hotel evolution over 40 years by applying big data and the ESTDA method. The systematic and evolutionary exploration will enable hotel researchers to understand the spatial–temporal nature of hotel distribution better. Introducing the ESTDA method into tourism and hotel research also provides an additional tool to researchers. Hotel investors and operators, city and tourism planners and market regulators can learn from the evolution of location patterns to make better where and when decisions.

The purpose of this paper is to take second-hand vehicles at judicial auctions in China as the primary research direction and to explore the impact of purchasing restriction policy and city size on the relationship between the appraisal price and transaction price of second-hand motor vehicles in the context of auto purchase restriction in China from a microscopic angle. It attempts to broaden the pricing ideas of judicial appraisal enterprises in providing appraisal prices of second-hand motor vehicles and to put forward suggestions for the optimization of appraisal prices and appraisal standards of judicial appraisal enterprises.

With the help of Python, this paper crawls 59,038 lines of valid data from three leading internet judicial auction platforms, namely “Ali Auction,” “China Beijing Equity Exchange” and “Gong Pai Wang,” as research samples. Besides, this paper forms a database containing judicial auction used car appraisal prices, transaction prices, motor vehicle purchase restrictions and whether the motor vehicle carries a license plate. By constructing a multiple regression model, the impact of automobile purchase restriction policy on the price of motor vehicles appraised by judicial appraisal enterprises is investigated.

With the help of the multivariate regression model, it found that under the same condition, the city where the auction took place implemented the automobile purchase restriction before the end of the auction. The court has specified that the buyer could directly obtain the license plate after the auction. The transaction price and the evaluation price ratio will be statistically larger, which proves that the license plate has an evident value in the transaction and is traded as subject matter by the residents, and consequently brings a higher premium to the price of automobile transaction in internet judicial auction. Meanwhile, the purchase restriction policy in the first-tier cities has resulted in a significant premium on automobile license plates, which is much higher than the automobile license plate premium level in non-first-tier cities under the same conditions.

Car ownership continues to rise with rapid economic development worldwide. Control the growth of car ownership, some countries and regions mainly restrict the issuance of motor vehicle license plates, which indirectly leads to vehicle license plate indicators becoming a scarce resource. National laws permit judicial auction as a means for the people's courts to settle creditors' claims in enforcement procedures of civil cases. In the judicial auction process, the People's Court introduces third-party evaluation enterprises to appraise, assess and audit the subject and obtain the appraisal price, which guides the bidding behavior of used car buyers and indirectly affects the transaction price of used cars.

As the only subject capable of assessing the value of used cars at judicial auctions, judicial appraisal enterprises have received widespread attention for their appraisal results. This paper researches this field by screening the factors affecting the ratio of motor vehicle transaction price to the appraised price. It also analyzes how the ratio of motor vehicle transaction price to appraised price is affected by motor vehicle purchase restrictions and the situation with license plates. This paper examines the existence of premiums for motor vehicle transactions with license plates, evaluates the purchase restrictions in cities with motor vehicle purchase restrictions and verifies that the premiums for motor vehicles at judicial auctions are affected by purchase restriction policies as well as the influence of city class. These studies have important implications for judicial appraisal enterprises to establish reasonable appraisal mechanisms and optimize appraisal prices. They also provide new ideas and methods for appraisal enterprises to assess the value of used vehicles at judicial auctions.

This paper aims to learn about consumers’ information disclosing patterns in the mobile internet context by investigating how demographic, geographic and psychological factors influence their information disclosing willingness (IDW).

Drawing on self-disclosure theory, the authors carried out simple linear regression analyses on a Chinese sample of 10,000 participants.

The results revealed that significant gender differences exist between males and females in their IDW in mobile internet context, and females have higher IDW than males do. And the authors also found that first-tier (third tier) citizens have the lowest (highest) IDW in their mobile internet usage.

This study offers three implications. First, this paper captures the insight of IDW within the mobile internet context, while previous studies mostly focus on the desktop internet context. Second, the results show that females have higher willingness to disclose than males do in the context of mobile internet, which is different from the findings of prior studies that females have higher privacy concerns and lower disclosing willingness in the context of desktop internet. Thirdly, this research introduces city tiers as a new approach to the study of IDW, which is one of the first studies exploring the geographical effect on information privacy.

This empirical study, from the international retailing perspective, examines the direction of retailers' further expansion after initial entry into overseas host market in the context of the luxury fashion retail market in China.

The research adopts qualitative multiple case studies.

After initial entry into China, luxury fashion retailers further expand their retail operations through three directional patterns: cautious, regional and countrywide expansions. The stepwise expansion from tier-1 to tier-2 and tier-3 cities remains popular; however, the importance of the tier system of Chinese cities has been weakened because tier-3 cities in affluent regions are perceived to have more potential than some tier-2 cities in less developed regions. The retailers assess a potential local market through interrelated criteria, including location and strategic importance, economic development, available store locations and staff, a high degree of urbanisation and tourism, debatable favourable policies and offers, and popularity of e- and m-commerce. There is a positive relationship between popularity of e- and m-commerce in a city and the potential of that city to run brick-and-mortar stores.

The paper offers an insight into the current international retailing literature by examining the direction of luxury fashion retailers' further expansion after their initial market entry. Particularly, the research considers a set of criteria which can be used to assess a potential local market, and the impact of e- and m-commerce on local market choices for brick-and-mortar stores.

The authors model heterogeneity of inflation expectations across Indian households using the Inflation Expectations Survey of Households data set. Using Carroll-type epidemiological models and pooled cross sectional analyses, the authors find that women, homemakers, older people and Tier 2 and 3 city dwellers tend to have higher inflation expectations compared to their counterparts. In the epidemiological model-based analysis, these very cohorts display higher speed of adjustment to news. Overall higher relative adjustment speeds point to the significance of central bank communications.