Showing papers in "International Journal of Business Forecasting and Marketing Intelligence in 2016"
TL;DR: In this article, the authors examined the empirical relationship between personality traits and investment intentions, mediated by attitude towards financial risk, using a sample of 313 Generation Y students from a technical institution of Allahabad, India.
Abstract: Individuals take investment decisions based on risk, return and time horizon of the investment. Personality types of individuals affect their attitude towards financial risk and in turn their investment intentions. The present study examines the empirical relationship between personality traits and investment intentions, mediated by attitude towards financial risk. The study utilises a sample of 313 Generation Y students from a technical institution of Allahabad, India. Our results show that the neuroticism, extraversion and openness to experience dimensions have perfect mediated relationship with short term investment intentions, mediated by attitude towards financial risk. Agreeableness has been found to exert a partial mediated relationship with short term investment intentions, while the conscientiousness dimension of personality type has not been found to be a significant predictor of short term investment intentions. Similarly, agreeableness has not been found to predict the long term investment intentions of individuals.
21 citations
TL;DR: In this article, the authors argue that firms in tourism supply chains will use their variable, renewable, inimitable and non-substitutable (VRIN) resources to develop tourism supply chain agility, i.e., they should be in a position to respond in a speedy manner to customer's requirements.
Abstract: Tourism supply chains need to be agile, i.e. they should be in a position to respond in a speedy manner to customer's requirements. Hence we argue in this study using resource-based view that firms in tourism supply chains will use their variable, renewable, inimitable and non-substitutable (VRIN) resources and non-VRIN resources to develop tourism supply chain agility. Further, we posit such tourism supply chain agility as a dynamic capability that may impart competitive advantage. Perceptual data were gathered from different entities in tourism supply chains and were analysed using PLS. Empirical findings based on 233 complete responses suggest VRIN and non-VRIN resources to as significant enablers of tourism supply chain agility and such a capability results in a competitive advantage for the associated supply chains. Further, our study revealed perceived environmental dynamism as a dominant moderator influencing the proposed linkages among resources and tourism supply chain agility.
14 citations
TL;DR: In this paper, a multi-item periodic review probabilistic inventory model in fuzzy environment is investigated, where a single source of the inventory model with zero lead time and varying order cost under two limitations, such as holding cost and safety stock.
Abstract: This paper investigates a multi-item periodic review probabilistic inventory model in fuzzy environment. Here, we have considered a single source of the inventory model with zero lead time and varying order cost under two limitations, such as holding cost and safety stock. By employing the fuzzy expectation and possibility/necessity measure, the fuzzy model is transformed into an equivalent deterministic non-linear programming problem. Finally, the model is illustrated with the help of numerical example and few sensitivity analyses are also presented for different parameter to show the validity of the proposed model.
9 citations
TL;DR: Simulation results show that VANFIS significantly improves forecasting performance in comparison to ANFIS, and does not take any actual data at any point of time as its input, but works completely in the virtual environment.
Abstract: Uncertainties and non-linearity associated with the stock index make it difficult to predict its behaviour and hence it remains a challenging task for researchers Newly developed intelligent machine learning techniques have been applied to this area and these have established as efficient forecasting models This paper presents a Virtual Adaptive Neuro-Fuzzy Inference System (VANFIS) for efficient forecasting of stock market indices VANFIS works in a virtual environment where the Adaptive Neuro-Fuzzy Inference System (ANFIS) is exposed to virtual data positions to infer the future stock price This model does not take any actual data at any point of time as its input, but works completely in the virtual environment To validate the performance of the proposed model, 15 years' data from ten stock markets are taken and five different performance metrics are evaluated Simulation results show that VANFIS significantly improves forecasting performance in comparison to ANFIS
7 citations
TL;DR: The main purpose of as mentioned in this paper is to study the effect of cause-related marketing on the consumer purchase intention, and the results revealed that cause related marketing also has effect on moral pleasure, brand attractions, and brand loyalty.
Abstract: The main purpose of this research is to study the effect of cause-related marketing on the consumer purchase intention. In this regard, cause-related marketing, moral pleasure, brand attraction, company-consumer identification, brand loyalty, and purchase intentions have been considered as the variables of this study. In order to collect the research data, a researcher-developed questionnaire has been used. The statistical population consists of the clients of the Ghalamchi centre for educational services in the city of Qom (Iran). To include the sample members, a sample consisting of 360 clients is randomly selected. The research data are analysed through Structural Equation Modelling (SEM) in the Amos18. The findings revealed that cause-related marketing does not affects the consumer purchase intention. Furthermore, cause-related marketing also has effect on moral pleasure, brand attractions, and brand loyalty.
7 citations
TL;DR: A new approach has been described to predict the purchase behaviour of online customer based on logistic regression and artificial neural networks which may help the e-retailing sites to design the suitable strategies.
Abstract: The purpose of this research is to identify the relationship among online purchasing behaviour of the customer with customer's personal characteristics, demographic and webographic traits and the web-store qualities. This study employs logistic regression and artificial neural networks to predict customer's online purchase behaviour. A comparison has been made between the results obtained by logistic regression and artificial neural networks. The proposed methodology provides a better understanding of the buying behaviour of an online customer. The study uses simple linear logistic regression which may be extended further with nonlinear regression. For a neural network model to be robust enough to produce better results, more training data are required. A new approach has been described to predict the purchase behaviour of online customer based on logistic regression and artificial neural networks which may help the e-retailing sites to design the suitable strategies.
7 citations
TL;DR: In this paper, the accuracies of different Grey system models such as GM(1,1), FRMGM(1.1), VGM and FRMVGM are investigated.
Abstract: A system containing known values and uncertain unknown values is called a Grey system. Grey system requires only a limited amount of data to estimate the behaviour of unknown systems with poor, incomplete or uncertain information. In this paper, the accuracies of different Grey system models such as GM(1,1), FRMGM(1,1), VGM and FRMVGM are investigated. In addition to this, Linear Regression model is also used for comparison. These Grey models solve complex and sophisticated problems like foreign currency exchange. Foreign currency exchange rates are affected by many highly correlated factors. These factors could be economic, political and even psychological factors, and each of them affect the rate of currency exchange in difference level from time to time. Foreign currency exchange rate from Commercial Bank of Ethiopia between November 2014 and October 2015 are used to compare the performance of different models. The simulation result shows that FRMGM(1,1) is the best in model fitting and forecasting foreign currency exchange.
3 citations
TL;DR: The research focused on evaluating and understanding the implications of using sales orders (shipments) to plan for a supply chain and found a statistically significant difference between the two series.
Abstract: Many firms use customer orders time series as the basis of their forecasting and demand planning. However, there are other firms that use sales orders (shipments). Our research focused on evaluating and understanding the implications of using sales orders (shipments) to plan for a supply chain. We evaluated the structural difference between customer orders time series and sales orders time series. An experiment was conducted using a set of 48-month and a set of 576-month (long) normally distributed, randomly generated customer orders time series and shipment time series. The time series were statistically evaluated periodically by rolling the data and then comparing them using a two-sample comparison in Statgraphics Centurion XVII software. The series were then used to generate periodic forecast and their forecasts statistically tested using two-sample comparison. We found a statistically significant difference between the two series for both the 48-period time series and the extended 576-period time series. Our results show that customer orders time series is statistically different from shipment timer series due to censorship. Forecasts generated from customer orders and sales orders time series exhibit statistically significant difference. Using shipment time series to forecast and plan for a demand-driven supply chain causes a perpetual state of under-inventory.
3 citations
TL;DR: In this article, the adoption of digital marketing strategies is viewed as a holistic process which encompasses motivational, emotional, and cognitive factors underlying the implementation of Digital marketing strategies to achieve research purposes.
Abstract: Existing research on digital marketing has mainly focused on social media However, internet evolution brings particular challenges that must be faced In order to explore new business opportunities, it becomes increasingly important to develop new conceptual models on the availability and adoption of digital marketing strategies to a more sophisticated application This paper views the adoption of digital marketing strategies as a holistic process which encompasses motivational, emotional, and cognitive factors underlying the implementation of digital marketing strategies To achieve research purposes it is presented a conceptual model to understand the attributes of digital marketing in building market competitiveness in Mexico This paper discusses the Technology Acceptance Model (TAM), the Theory of Reasoned Action (TRA) and the Diffusion of Innovations Theory as the base to develop the research model and analyses the unique business dynamics of the current digital environment in emerging markets The paper concludes with a discussion on its conceptual contributions, conclusions and interesting directions for future research
2 citations
TL;DR: In this article, the Tehran Stock Exchange Price Index (TEPIX) is estimated and forecasted using daily data for the period 22 May 2011 to 11 August 2011 to achieve that goal, various forecasting methods will be applied, including ARIMA, FarimA, ANN and ANFIS models Comparing the forecast accuracy of the models mentioned above, using forecast accuracy measures such as RMSE, MAE, MAPE and U-Thiel implied that the combined models of ANFis and FARIMA have outperformed other models of forecasting daily stock indices
Abstract: Forecasting economic and financial variables is of high interest to economic policy-makers in all countries In this paper, the Tehran Stock Exchange Price Index (TEPIX) is estimated and forecasted using daily data for the period 22 May 2011 to 11 August 2011 To achieve that goal, various forecasting methods will be applied, including ARIMA, FARIMA, ANN and ANFIS models Comparing the forecast accuracy of the models mentioned above, using forecast accuracy measures such as RMSE, MAE, MAPE and U-Thiel implied that the combined models of ANFIS and FARIMA have outperformed other models of forecasting daily stock indices However, statistical comparison of forecast accuracy of different models using statistics such as Harvey, Leybourne and Newbold shows no significant difference between the forecast accuracy of these models
2 citations
TL;DR: In this paper, the authors explore and propose the role of outcome, interaction, and environmental quality in the interfaces gap of service quality, in the presence of third party logistics on supply chain competitiveness with mediating role of relationship quality.
Abstract: The aim of study is to explore and propose the role of outcome, interaction, and environmental quality in the interfaces gap of service quality in the presence of third party logistics on supply chain competitiveness with mediating role of relationship quality. It is a propositional paper, in which the implications of service quality parameters in the interfaces within the supply chain are hypothesised and proposed to study and empirically investigated in future. A very few studies of service quality in the context of whole supply chain integration, collaboration, and performance exist in the supply chain literature. This study posits a significant contribution towards the managing service quality within supply chain context.
TL;DR: In this paper, the authors investigate the impact of competition on the acquisition of technology in Nigeria and find that competition has a positive and significant impact on technology acquisition among Nigerian firms, while imperfectly competitive markets are better at stimulating innovative activity.
Abstract: Scholarly investigations into the impact of competition on innovative activities have provided mixed results which range from finding that imperfectly competitive markets are better at stimulating innovative activity to finding the complete opposite Most of these studies have been carried out in developed economies, with little evidence on developing countries, especially Nigeria This study seeks to provide empirical evidence on how firms in Nigeria respond with respect to the acquisition of technology when they face competition Competition in this context is defined by the Price-Cost Margin (PCM) and technology acquisition is derived by summing expenditure on R&D, technical fees/licenses and royalty payments The data obtained from 42 manufacturing firms listed on the Nigerian Stock Exchange between 2001 and 2013 was analysed using the Arellano and Bond Generalised Method of Moments (GMM) technique The result shows that competition has a positive and significant impact on technology acquisition among Nigerian firms
TL;DR: In this article, the authors present the current status of use of social networking sites particularly Facebook by the public and private sector banks in India and present a survey of Facebook pages of 47 banks explored during the period of February-March 2015.
Abstract: The paper presents the current status of use of social networking sites particularly Facebook by the public and private sector banks in India. The data for this study is based upon a survey of Facebook pages of 47 banks explored during the period of February-March 2015. The paper is based on an instrument called Facebook Assessment Index (FAI) developed by Miranda et al. (2013), which uses three categories to evaluate the essential information on a firm's Facebook page: popularity, interactivity and content. The results found that only 48.9% of the banks observed had their official Facebook page. Amongst, the three measures of FAI, new private sector banks (ICICI Bank and Axis Bank) performed well as compared to other banks. In general, the banks were not fully harnessing the utility of Facebook and a great opportunity exists for the banks for improvement in their usage of Facebook.