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The purpose of this paper is to investigate customers' intentions to purchase mobile communications services and how these intentions are affected by the customers' price perceptions in two customer segments – a mobile segment and a combined segment. A further aim was to gain insight into the formation of price perceptions, and customer characteristics that underlie the differences between purchase intentions and price perceptions.

The study was conducted in the Finnish mobile services market. The sample data were collected through a postal survey (n=3,000) sent to customers of a Finnish teleoperator. In analyzing empirical data the explanatory factor analyses, linear regression analyses, and analysis of variance were applied.

The results indicated that a significant and positive relationship exists between customers' price perceptions and their purchase intentions, and that the formation of price perceptions is significantly influenced by satisfaction with pricing and services. Price transparency was found to be negatively associated with customers' price perceptions. Gender, age, and experience of service use were found to explain the differences in customers' perceptions.

By segmenting customers according to the research results and targeting pricing schemes specific to these segments would potentially improve customers' price perceptions and their intentions to purchase mobile services. The study also supported the use of multi‐dimensional pricing schemes as it was found to positively influence customers' price perceptions.

This paper provides new practical and theoretical insights into the relationship between purchase intentions and price perception, and into the formation of the price perceptions of mobile services customers.

Price sensitivity is one of the key factors affecting to companies pricing choices. Yet in mobile services sector business practitioners are facing problems in pricing decisions as they are short of knowledge on their customers’ price sensitivity levels and dynamics. Therefore this study aims to focus on this unexplored field in order to provide more accurate tools for mobile service providers to price their services more effectively.

This study is conducted on Finnish mobile services markets. The focus is on examining how customers’ price sensitivity differs between different customer segments and which factors affect to the price sensitivity levels. The sample data is collected through a quantitative postal survey in which 3,000 questionnaires was sent to mobile service customers of a Finnish teleoperator. In analyzing the empirical data the explanatory factor analysis and multiple regression analysis was applied.

It was discovered that mobile service customers differ significantly in their price sensitivity levels; customers with moderate usage of mobile services are least price sensitive, while intensive and low‐end users are most sensitive to price changes. Important was also the notion that customers’ price perceptions and innovativeness levels were accurate indicators of their price sensitivity.

This paper has concentrated only on Finnish mobile services markets. In order to construct a robust set of indicators for international use, cross‐cultural study on testing the factors of this study should be conducted.

For business practitioners, the most distinctive finding of this paper are a new set of factors through which segmenting of their customers can be made more accurately.

With the findings of this paper a mobile service provider is able to increase efficiency of pricing of mobile services.

This paper presents a model relating Nagle and Holden's factors of price sensitivity to expected price and willingness to pay. This work presents various perspectives on price elasticity/sensitivity, empirically tests aspects of the influence of perception of the offer (product/service) on expected price, and illustrates how the pricing methods developed within provide quantitative precision to the practice of price setting by capturing perceptions important to consumers.

The authors used a within‐subjects design to study four brands in two product categories, automobiles and computers. Model evaluation employs ordinary least squares regression.

Ten qualitative factors were studied. Overall, the results show four factors predict expected price for the target market, product and brand. The factors are perceived substitutes, quality, fairness, and unique value.

This research makes the following contributions. First, the authors are able to quantify ten factors of price sensitivity relevant to the evaluation of product pricing. Second, they are able to identify the relevant factors of price sensitivity for two product categories specific to a given target market. Third, they provide a data‐driven model that enables translation of pricing variables into quantitative values to arrive at the price of a product. The major theoretical contribution of this paper is to show that Nagle and Holden's ten factors of price sensitivity may act in the following way: the change in product/service perception may influence expected price, and then the change in expected price influences willingness to pay. The empirical focus of the current research is on the first of these two changes.

The purpose of this paper is to examine whether there is a systematic real estate risk factor in retail firms' common stock returns and whether this risk is priced in the stock market. In addition, whether the real estate risk sensitivities of retail stocks are linked to each firm's real estate intensity is investigated.

With a sample of 556 retail firms from 15 countries and a three‐index model with a domestic stock market and a retail market factor, as well as a real estate risk factor as the three explanatory variables, the paper appeals to the maximum likelihood methodology of Gibbons which estimates factor sensitivity coefficients and factor risk premia simultaneously using an iterative seemingly unrelated regression (ITSUR) technique, as well as the generalized method of moments (GMM) procedure. In addition, the paper investigates whether the individual retail firms' real estate βs are affected by the firms' CRER levels and other financial characteristics, using instrumental variables estimation technique via three‐stage least squares (3SLS).

The paper finds property market risks carry positive risk premia after controlling for sensitivities to general market and retail market risks, implying that real estate is an important factor priced in the stock market value of the sample retail firms. However, higher real estate concentration does not necessarily cause higher real estate exposure after controlling for firm size, leverage and growth, implying that stock market investors are unwilling or unable to understand and capture the full risk real estate ownership risk in corporate valuation.

From the corporate management viewpoint, those retail firms with a significant real estate portfolio should always consider the “real estate exposure” factor in their overall corporate strategy. Their high real estate exposure renders them vulnerable to shocks in the real estate market.

The paper offers insights into whether real estate is an important factor in corporate valuation

This paper aims to investigate the behavior of volatility of Islamic equity indices toward fundamental risk factors. It focuses on the degree and structure of sensitivity to commodity price changes, global risk perception and term premium and whether crises and fragility periods have shaped the degree and structure of this sensitivity.

Quantile regression incorporating structural changes and GARCH-class model are used to establish how sensitivities are varying across volatility distribution depending on global events. The data are daily series of return indices, over the period spanning from January 1, 2001 until January 22, 2018.

The results show significant sensitivity to fundamental factors. The sensitivity is identified for different regional indices and intensified across quantiles. Speculation has shaped the structure of sensitivity at normal time, but correction holds at time of crisis. The results reveal that even if they share common features, commodities cannot be considered as homogeneous asset class. Indeed, the exact relationship cannot be observed at normal time in presence of speculation and information delay. However, at time of financial fragility and periods of crisis, the sensitivity is assigned with the plausible sign.

The obtained results present several policy implications as well for academics, portfolio managers and policy-makers. It opens new research paths for academic research, it helps in investment decisions, provides lessons for portfolio diversification, both for price discovery and hedging. The results serve as well to implement effective macroeconomic stabilization policies and even fiscal policies to counteract any inflationary impact of fundamental price changes on investors and Islamic banks.

This paper contributes to empirical literature by dealing with the sensitivity of Islamic equity indices to commodity prices and term premium along with the effect of investor sentiment. It pays attention to the financial stability of Islamic stock markets by investigating the sensitivity at normal time, during fragility periods and periods of crisis. It considers the financialization process of commodity markets and includes the term premium to control for rational expectations on term structure of interest rates and the VIX (Volatility index) as global risk perception to control for safety and risk aversion.

The purpose of this paper is to examine whether the sensitivity of investment to cash flow varies with exogenous financial conditions.

A dynamic model of investment based on the Euler equation approach is employed to investigate the impact of macro-financial factors on the sensitivity of investment to cash flow. The sample comprises data from 84 non-financial firms listed on Saudi stock market over the period 2007–2018.

The results show that the sensitivity of investment to cash flow is positive, implying the presence of financing constraints for Saudi firms. Evidence also reveals that better financial conditions relax firms' financing constraints. However, contractionary monetary policy, poor financial development and liquidity crisis strengthen the dependence of firms on internally generated funds when undertaking new investment projects.

The empirical results have useful policy implications. First, policymakers should pay attention to the importance of policymaking based on the monetary demand of microeconomic entities. In monetary contraction periods, firms face greater challenges in accessing external finance. These firms are likely to experience under-investment which at a macro level would translate into lower investments and economic growth for the country. Second, policymakers are encouraged to implement complementary measures that, coupled with existing financial reforms, may promote efficiency, competitiveness and transparency in firms' operations. Finally, managers and investors should consider financial structure and condition as important factors in their investment decision.

This study extends previous research by investigating whether the widely reported positive investment and cash flow relationship can be observed using data from an emerging market, specifically Saudi Arabia. It also sheds light on the investment-cash flow debate under a macroeconomic perspective and provides further evidence on the impact of financial crisis on the investment-cash flow (ICF) sensitivity.

The purpose of this paper is, to study macroeconomic risk factors driving the expected stock returns of listed private equity (LPE). The authors use LPE indices divided into different styles and regions from January 2004 to December 2016 and a set of country stock indices to estimate the macroeconomic risk profiles and corresponding risk premiums. Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market βs that are greater than 1. A one-factor asset pricing model using world stock market returns as the only possible risk factor is rejected on the basis of generalized method of moments (GMM) orthogonality conditions. In contrast, using the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of economic policy uncertainty as additional risk factors, this multifactor model is able to price a cross-section of expected LPE returns. The risk-return profile of LPE differs from country equity indices. Consequently, LPE should be treated as a separate asset class.

Following Ferson and Harvey (1994), the authors use an unconditional asset pricing model to capture the structure of returns across LPE. The authors use 11 LPE indices divided into different styles and regions from January 2004 to December 2016, and a set of country stock indices as spanning assets to estimate the macroeconomic risk profiles and corresponding risk premiums.

Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market ßs that are greater than 1. The authors estimate a one-factor asset pricing model using world stock market returns as the only possible risk factor by GMM. This model is rejected on the basis of the GMM orthogonality conditions. By contrast, a multifactor model built on the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of global economic policy uncertainty as additional risk factors is able to price a cross-section of expected LPE returns.

Given data availability, the authors’ sample is strongly influenced by the financial crisis and its aftermath.

Information about the risk profile of LPE is important for asset allocation decisions. In particular, it may help to optimally react to contemporaneous changes in economy-wide risk factors.

To the best of authors’ knowledge, this is the first LPE study which investigates whether a set of macroeconomic factors is actually priced and, therefore, associated with a non-zero risk premium in the cross-section of returns.

Clarifying the risk evolution mechanism of housing construction for work-safety management is essential. Existing studies have inadequately discussed the risk-accumulation process in housing construction. Therefore, this study aimed to use the complex network theory and risk allocation mechanisms to explore the evolution of risk factors.

The authors analysed a database of housing construction accidents in China from 2015 to 2020 to identify risk factors. Moreover, the causal relationship between risk factors was determined through a systematic analysis of the logical sequence of risk factors. A complex network was used to construct a risk network for housing construction accidents (RNHCA).

The risk matrix method was used to define the factor risk threshold, and a risk value was assigned based on the correlation between risk factors. This contributes to the examination of the evolution mechanism of risk networks in the process of risk factor transmission. The case verification results show that the RNHCA quantitative assessment model can better evaluate the system risk status of housing construction accidents. Furthermore, this model can identify the key risk factors and risk chains with high risk in the evolution of the risk network.

Accident investigation reports need to be classified and processed to analyse the evolution law of risk networks under different scales of construction project, such as high-rise buildings, middle-rise buildings, and low-rise buildings.

This study clarified the risk evolution process of complex systems in housing construction and provided a new method for analysing accidents.

This study clarifies the risk value allocation of risk factors in the transmission process and reveals the process of risk factor evolution in housing construction. This study explains the individual risk factors that form a systemic risk through the transmission chain. Moreover, this paper clarified the transformation relationship between system risk and accidents. The paper also provided a new perspective for risk analysis.

Human error is among the leading causes of construction-based accidents. Previous studies on the factors affecting human error are rather vague from the perspective of complex and changeable working environments. The purpose of this paper is to develop a dynamic causal model of human errors to improve safety management in the construction industry. A theoretical model is developed and tested through a case study.

First, the authors defined the causal relationship between construction and human errors based on the cognitive reliability and error analysis method (CREAM). A dynamic Bayesian network (DBN) was then developed by connecting time-variant causal relationships of human errors. Next, prediction, sensitivity analysis and diagnostic analysis of DBN were applied to demonstrate the function of this model. Finally, a case study of elevator installation was presented to verify the feasibility and applicability of the proposed approach in a construction work environment.

The results of the proposed model were closer to those of practice than previous static models, and the features of the systematization and dynamics are more efficient in adapting toward increasingly complex and changeable environments.

This research integrated CREAM as the theoretical foundation for a novel time-variant causal model of human errors in construction. Practically, this model highlights the hazards that potentially trigger human error occurrences, facilitating the implementation of proactive safety strategy and safety measures in advance.

Service quality (SQ) has become an essential and indispensable component in healthcare and many other industries. SQ can deliver guaranteed stakeholder value and consequent consumer delight in the healthcare sector. The purpose of this study is to identify the relationships of various SERVQUAL elements with respect to the SQ of surgical instrument suppliers among surgeons.

Data were collected from a sample of 112 surgeons working in the USA using the “snowball sampling” technique. A few standardised questionnaires, including SERQUAL, were used to collect the data. R-programming was used to perform structural equation modelling (SEM) analysis on the collected data.

The research study identified that service delivery factors and the SQ of surgical instruments contribute significantly towards medical practitioner sensitivity in the US healthcare industry. Word of mouth (WOM) did not have any significant impact on the medical practitioners' sensitivity.

A review of related literature revealed that studies that examine the surgeon's perspectives of SQ are scarce. Thus, the present study is directed towards this gap in literature. The findings of the study are significant in nature and have made a substantial contribution to management literature.