Template-Type: ReDIF-Article 1.0 Author-Name: Samin Javanmardi Author-X-Name-First: Samin Author-X-Name-Last: Javanmardi Author-Name: Ali Haj Aghapour Author-X-Name-First: Ali Haj Author-X-Name-Last: Aghapour Author-Name: Suhaiza Zailani Author-X-Name-First: Suhaiza Author-X-Name-Last: Zailani Author-Name: Abdollah Naami Author-X-Name-First: Abdollah Author-X-Name-Last: Naami Title: Identification of critical success factors for mobile apps: a stakeholder-Delphi study Abstract: The ongoing growth of the smartphone market has drawn considerable interest in the mobile app development industry among individual publishers, small organisations and even large software companies. Iran, as the 12th country with the highest number of active smartphone users, has a thriving market for mobile app developers. Despite the market growth, this area has received little academic attention within business management literature. This paper represents the results of a qualitative study of a two-round Delphi process after providing a critical review of literature. The results suggest a critical success factor (CSF) framework in nine dimensions consisting of 19 critical factors for mobile apps success in Iran. These findings help mobile app developers to optimise their limited resources on those critical factors that are more likely to bring success to their products and business. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 207-240 Issue: 3 Volume: 7 Year: 2022 Keywords: app; application development; critical success factors; CSFs; Delphi; mobile app; smartphone; stakeholder theory; qualitative approach. File-URL: http://www.inderscience.com/link.php?id=122894 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:3:p:207-240 Template-Type: ReDIF-Article 1.0 Author-Name: Masha Ahoba Buah Author-X-Name-First: Masha Ahoba Author-X-Name-Last: Buah Author-Name: Victor Amoako Temeng Author-X-Name-First: Victor Amoako Author-X-Name-Last: Temeng Author-Name: Samuel Kwesi Asiedu Addo Author-X-Name-First: Samuel Kwesi Asiedu Author-X-Name-Last: Addo Author-Name: Yao Yevenyo Ziggah Author-X-Name-First: Yao Yevenyo Author-X-Name-Last: Ziggah Title: Application of extreme value theorem in modelling oil consumption of organisation of petroleum exporting countries Abstract: In this study, oil consumption of organisation of petroleum exporting countries (OPEC) from 1973 to 2018 is modelled using extreme value theorem (EVT). The main objective of this paper was to employ both the block maxima method and peak over threshold method to determine the best fitting distribution to extreme oil consumption of OPEC. In both approaches, the maximum likelihood estimation was applied to determine the distribution parameters. Findings from the study revealed that the optimal model from the generalised extreme value (GEV) distribution was the Weibull distribution with shape, scale, and location parameter values of -0.63, 6,217.54 and 26,773.21. The optimal model from the generalised Pareto distribution (GPD) was Pareto type II distribution with shape and scale parameters of 0.04 and 666.64 at a threshold value of 34,000. A comparison of the return levels revealed that GPD gave higher return level estimates than GEV. In the study, GEV was chosen over GPD because the difference between the 95% lower and upper confidence intervals and the actual return level for the BMM was found to be lower as compared to the POT approach. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 259-276 Issue: 3 Volume: 7 Year: 2022 Keywords: block maxima method; BMM; peak over threshold; POT; Weibull distribution; return period. File-URL: http://www.inderscience.com/link.php?id=122899 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:3:p:259-276 Template-Type: ReDIF-Article 1.0 Author-Name: Mehir Kumar Baidya Author-X-Name-First: Mehir Kumar Author-X-Name-Last: Baidya Author-Name: Bipasha Maity Author-X-Name-First: Bipasha Author-X-Name-Last: Maity Title: Managing marketing mix competition dynamics Abstract: Studies suggest that competition is inevitable as well as spoils brand performance. There are various forms of competition between brands. This study attempts to understand of marketing mix competition between brands in a mature product category. Three primary and 12 secondary hypotheses were framed. Panel data on sales and marketing mix variables were gathered from ten brands in a CPG category over a period 2013-2018 in India. Thereafter, multivariate autoregressive integrated moving average with predictors model (MARIMAXM) and double-log regression model (MRM) were fitted to data. All hypotheses such as 'asymmetries in cross effects' are validated. The findings should assist managers in deciding whether to react or not react to competition using the tested evidence. This paper contributes to marketing practice and research because it produces insights into competitive structure and its evolution over time. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 277-294 Issue: 3 Volume: 7 Year: 2022 Keywords: marketing mix; competition; economic; dynamics. File-URL: http://www.inderscience.com/link.php?id=122900 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:3:p:277-294 Template-Type: ReDIF-Article 1.0 Author-Name: Nahid Jafari Author-X-Name-First: Nahid Author-X-Name-Last: Jafari Title: The chaos on US domestic airline passenger demand forecasting caused by COVID-19 Abstract: Commercial aviation is a major contributor to the US economy, directly or indirectly generating approximately US$680 billion, or 4% of GDP, and supporting millions of jobs. Approximately 965 million passengers flew to US destinations in 2017 (https://rosap.ntl.bts.gov/view/dot/37861). Given the importance of the industry, accurate forecasting of air passenger demand is valuable, and the most sophisticated forecasting technologies can be applied to this endeavour. The ongoing COVID-19 crisis has had an unprecedented impact on air traffic. Effective forecast of passenger demand would benefit airlines to develop adequate recovery plans and prevent (or minimise) any catastrophe in handling passengers during and post pandemic. The purpose of this study is to investigate COVID-19's impact on the US domestic air passengers demand, identify the most influential features on air passenger demand, and design more accurate forecast models. In addition, we address a computational challenge in developing forecasting models due to the volatility of the recent data as a result of the COVID-19 crisis. We use both traditional and artificial intelligence methods and discuss their capabilities to handle the challenge. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 241-258 Issue: 3 Volume: 7 Year: 2022 Keywords: air passenger demand; the US airlines market; seasonal time series forecasting; deep learning; gated recurrent units. File-URL: http://www.inderscience.com/link.php?id=122901 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:3:p:241-258 Template-Type: ReDIF-Article 1.0 Author-Name: Jaydip Sen Author-X-Name-First: Jaydip Author-X-Name-Last: Sen Title: A forecasting framework for the Indian healthcare sector index Abstract: Forecasting of future stock prices is a complex and challenging research problem due to the random variations that the time series of these variables exhibit. In this work, we study the behaviour exhibited by the healthcare sector's time series of India in the Bombay Stock Exchange (BSE). We collect the historical monthly index values of the BSE S&P healthcare sector from January 2010 to December 2021. The time series is decomposed into its three components trend, seasonality, and random. The component values reveal some important characteristics of the sector in the pre-pandemic and peri-pandemic times. We also propose five predictive models based on the exponential smoothing and autoregressive integrated moving average techniques for forecasting the monthly index values of 2021 based on the historical index values from January 2010 to December 2020. Extensive results are presented on the performances of the models. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 311-350 Issue: 4 Volume: 7 Year: 2022 Keywords: time series decomposition; trend; seasonality; randomness; exponential smoothing; HoltWinters forecasting; autoregressive integrated moving average; ARIMA; root mean square error; RMSE; mean absolute percentage error; MAPE. File-URL: http://www.inderscience.com/link.php?id=125783 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:4:p:311-350 Template-Type: ReDIF-Article 1.0 Author-Name: Bui Nhat Vuong Author-X-Name-First: Bui Nhat Author-X-Name-Last: Vuong Title: A model of factors affecting drugstore cosmetics repurchase intention through Facebook social media: an evidence from Vietnam Abstract: The objective of this study is to build the model to investigate the online repurchase intention of cosmetic consumers in the context of drugstore cosmetics widely sold on Facebook in Vietnam. By conducting the survey, this study collects data from the respondents in the 18-35 age group and having bought drugstore cosmetics on Facebook in Vietnam. The study uses SPSS 20 and AMOS 24 to analyse the data. The findings of the study reveal some noteworthy points: 1) online relationship quality, consumer attitudes, and repurchase intention having a strong relationship with each other; 2) perceived enjoyment and subjective norm positively affecting consumer attitude; 3) perceived website usability positively influencing online relationship quality. Through the findings, the study would give some strategic recommendations so that the cosmetic stores on Facebook can make further improvements for consumer experiences on their websites, which partly helps them increase sales volumes and achieve sustainable development. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 362-374 Issue: 4 Volume: 7 Year: 2022 Keywords: repurchase intention; online relationship quality; perceived website usability; perceived enjoyment; Vietnam. File-URL: http://www.inderscience.com/link.php?id=125784 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:4:p:362-374 Template-Type: ReDIF-Article 1.0 Author-Name: Dag Øivind Madsen Author-X-Name-First: Dag Øivind Author-X-Name-Last: Madsen Author-Name: Kåre Slåtten Author-X-Name-First: Kåre Author-X-Name-Last: Slåtten Title: An exploratory bibliometric analysis of research on Blue Ocean Strategy Abstract: Blue Ocean Strategy is a strategy concept that was introduced during the mid-2000s. Although the concept has received much attention in the business world, it has to a large extent been ignored by strategy and management scholars. This paper carries out an exploratory bibliometric analysis of research on Blue Ocean Strategy, intending to identify the most influential journals, documents, authors, and countries. The paper provides a preliminary overview of the current state of research on Blue Ocean Strategy and can thus serve as a starting point for more in-depth analyses. It also provides a reading list for researchers, students, and practitioners new to the concept of Blue Ocean Strategy. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 295-310 Issue: 4 Volume: 7 Year: 2022 Keywords: Blue Ocean Strategy; BOS; bibliometrics; management concept; strategic management; management fashion. File-URL: http://www.inderscience.com/link.php?id=125787 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:4:p:295-310 Template-Type: ReDIF-Article 1.0 Author-Name: Dipanjan Bhowmick Author-X-Name-First: Dipanjan Author-X-Name-Last: Bhowmick Title: Impact of brand design on consumer perception and decision making Abstract: The research focuses on understanding the purpose of branding and ways to do it effectively to improve influence over the consumer. The perception built in the consumer's mind triggers decision making from the consumer's end. The study shows the brand's strength that has been built by a company through its branding strategy and the consumers over which the brand has the control to influence based on different categories they belong to. This will help a company assess and improve its branding and influence consumer perception and decision making. The study provides ideal outcomes which will suit the branding environment the best and provide the maximum output that is suitable and manageable for the company in the long run. The research also draws inference backed by data collected through surveys that price is influenced by brand design. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 375-386 Issue: 4 Volume: 7 Year: 2022 Keywords: branding; decision making; consumer perception; pricing; visual design. File-URL: http://www.inderscience.com/link.php?id=125791 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:4:p:375-386 Template-Type: ReDIF-Article 1.0 Author-Name: Rekha Joshi Author-X-Name-First: Rekha Author-X-Name-Last: Joshi Author-Name: Aditi Sahni Author-X-Name-First: Aditi Author-X-Name-Last: Sahni Author-Name: Manjary Chaudhary Malik Author-X-Name-First: Manjary Chaudhary Author-X-Name-Last: Malik Title: Consumer awareness regarding harmful chemicals in everyday products Abstract: High-risk chemical substances in everyday products can have a terrible impact on human health and the environment. Such chemicals can contain a variety of harmful substances that may be neglected by most consumers. Consumer awareness has prompted businesses to substitute less harmful alternatives. Many chemical substances, such as preservatives in cleaning agents, perfumes in personal care products, and others, are found in daily household products and have become a worrying concern as consumers' awareness has increased. This has also become an alarming issue due to consumers' increased awareness regarding chemicals. The present study was conducted on 100 consumers using a well-structured questionnaire in the Nainital District of Uttarakhand using the convenience random sampling method. The study's findings revealed that the majority of respondents were aware and seriously concerned that the products they used everyday had chemicals that may have affected their health and the environment. Journal: Int. J. of Business Forecasting and Marketing Intelligence Pages: 351-361 Issue: 4 Volume: 7 Year: 2022 Keywords: consumers; consumer awareness; hazardous chemicals; consumer products. File-URL: http://www.inderscience.com/link.php?id=125793 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:4:p:351-361