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This study aims to identify individuals' biases while making investment decisions and explore how these biases can be incorporated into a robo-advisory platform to help mitigate these biases. This paper identifies eight investment-related behavioral biases: mental accounting, gambler’s fallacy, hindsight, regret aversion, disposition, trend-chasing, loss aversion and herding.

This study uses primary data from 263 respondents across various age groups, of which approximately 50 were wealth management professionals in the UAE. A random sampling method from probability sampling is employed to gather the primary data. The identified biases serve as dependent variables; the age and income of individuals serve as the independent variables.

Age and income are significantly related to mental accounting, herding, gambler fallacy and loss aversion. Existing studies on behavioral finance demonstrate that individuals who make investment decisions are susceptible to cognitive fallacies, leading to nonrational investment decisions.

By studying these biases affecting individuals of varying ages and income levels, wealth management professionals can tailor their financial robo-advisory services to address these biases and help clients build wealth with consistent investment.

This study uses survey-based sampling in the context of the UAE; hence, the data and analysis represent originality.

The aim of this research is to re-examine the dynamic linkages between macroeconomic variables and the stock market indices in Malaysia following some transformational changes in the policies and the exchange rate regime.

Using monthly data points for all the economic variables and the stock market index (KLCI Index), the authors applied vector autoregression (VAR) model to examine the relationship. The authors also used impulse response function (IRF) in order to explore the effect of one-unit shock in “X” on “Y” under the VAR environment.

The authors' study finds a significant relationship between all the macroeconomic variables and the stock market index of Malaysia. The cointegration results indicate a long-term relationship, whereas the vector autoregressive-based impulse response analysis suggests that the Malaysian stock index (KLCI) responds negatively to the money supply, inflation and producer price index (PPI). However, the authors' results indicate a positive response from the stock index to the exchange rate.

The authors' study's results are based on selected macroeconomic variables and the VAR model. Researchers may find other variables and methods more useful and may provide findings accordingly.

Since the results are quite asymmetric, it would be interesting for the market players, policymakers and regulators to consider the findings and explore appropriate opportunities.

While the relationship between macroeconomic variables and stock market indices has been widely examined, a significant gap in the literature remains concerning the role of exchange rate variable on the stock market in an emerging economy context.

The aim of this research is to explore multiscale hedging strategies among cryptocurrencies, commodities, and GCC stocks. Particularly, this is done by evaluating the connectedness among these asset classes covering a period with COVID-19 implications. Using the wavelet approach, the present study aims to recommend whether there exist different time horizon-based hedging abilities across the asset classes.

The approach used in this study is a multiscale decomposition of time series based on wavelets of daily prices of 13 asset classes. Since the wavelet analysis allows to decompose the time series into its frequency components at different time scales by a filtering process the study covered 1-day, 8-day, and 64-day time horizons to examine the hedging properties across those asset classes.

The results of this study show that hedging effectiveness differs among stock markets over time. In some cases, cryptocurrencies may keep their hedging properties across time while in others they switch from safe haven to hedge devices. In almost all cases, the three main cryptocurrencies showed diversifying properties as was observed by the multiscale correlation and hedge ratio estimations. In a competing sense, gold showed safe haven properties across time than cryptocurrencies except at an 8-day time scale where hedge ratios were low, positive and statistically different from zero that could be interpreted as a good hedge device in the medium term.

Though this research has considered a set of thirteen asset classes, it was limited to a period in which most cryptocurrencies started trading for the first time which reduces the number of observations compared to Bitcoin prices and stable coins such as Ethereum, Ripple, and Bitcoin Cash. Also, the research was focused on the GCC stock markets which may have different results as compared to other regional markets of Asia or Latin America. A comparative analysis in future could be another area of research in future.

This study has some significant policy implications. The cryptocurrency market is severely affected by demand and risk shocks to crude oil prices during the COVID-19 period. From the investor's point of view, diversification benefits can be obtained by combining cryptocurrencies along with oil-related products during episodes of financial turmoil and COVID-19 pandemic. The GCC region is constantly endeavoring to adopt more scientific tools and mechanisms of investment, and therefore, this study's results will provide some useful directions to the government, policymakers, financial institutions, and investors.

The current study covers a big bunch of 13 assets spanning across financial and real assets. This is based on literature gap and hence, will be a significant addition to the existing literature. Moreover, the GCC region is emerging as a global investment hub and this study will provide investors dynamic hedging strategies across these asset classes.

ABS Tyres was a medium sized 2-wheeler tyre manufacturer which sold most of its tyres through the OEM channel (sale of tyres fitted in new vehicle). It had minimal presence in the replacement market, the direct to consumer market for tyres. The management felt that an evaluation of the market opportunity in the replacement tyre market was necessary to improve the performance of the company while maintaining the lead in the Original Equipment market. It needed help in drawing up an appropriate market study to find out the opportunity.

The case is about a service provided to rail commuters who lack the time to attend to their daily chores because of the long hours spent in commuting. It talks about the process of building the business of providing a laundry pick up and drop off service at the railway station. The case may be a good starter for defining the business in terms of customer need served and how the entire operation is aligned towards addressing the need.

The case tells the story of a first generation entrepreneur, Dhirendra Singh, and his struggle for 15 years to establish a mango pulp based beverage marketing company without any external support and funding. The case highlights the travails that Dhirendra goes through in marketing an undifferentiated product, a mango drink. He survives, largely due to his grit and some lucky breaks, until an external funding agency notices him 15 years after he started his journey.

With growth and stability (in 2017, it was the fourth largest packaged beverage in India) come new issues for the enterprise to grapple with. The case leaves the reader to reflect upon these challenges that the company encounters. Can the company overcome these hurdles and thrive? How, is the question that remains unanswered.

We describe the application of a nested logit function for modelling consumer brand choice using household transaction data from the Indian market. This is unique since it is one of the first attempts to integrate disparate consumer information sources available at various levels of aggregation towards developing a prediction model for brand market share in India. We test the usefulness of the model for forecasting brand market share in the premium detergents market in Mumbai, India. The results of the model building exercise reveal the importance of advertising, specifically the role of ad message in influencing brand choice. It is concluded that such modelling initiatives show significant returns for market planning exercises in developing markets. However, the need for streamlining the collection of market data and its subsequent organization in a form that can help develop more portent prediction models is apparent.

Existing literature offers conflicting evidence on how prior product knowledge influences amount of information search. A majority of these studies are based on variants of cost benefit frameworks where consumers engage in search until the benefits from information search exceed search costs. The purpose of this paper is to develop an expectancy theory‐based framework to model consumers' information search and its antecedents, including motivation to search as an intervening construct.

The framework is tested using data from real consumers engaged in their actual purchase decisions, in an emerging market context, using longitudinal survey research design. The data are analysed using structural equation modeling to test the hypothesized model. The model shows an acceptable fit with X2 (271, 487)=640.252, p < 0.00 and 0.95 CFI.

Results indicate that the relationship between prior product knowledge to information search is mediated by motivation to search. Prior product knowledge influences motivation to search through its influence on the consumer's perceived ability to search and his/her perceived value of additional information. Furthermore, perceived ability to search is the strongest predictor of motivation to search. The parsimony of the proposed framework in providing a simpler account of factors influencing the search process along with its managerial implications is discussed.

The findings suggest that perceived ability to search and perceived value of additional information are two important levers that managers could use for achieving desired results. Furthermore, perceived ability to search is an important mediator, which completely mediates the relationship between prior product knowledge and motivation to search. These findings also provide strong indications about the need to simplify the search process for consumers, especially in the context when novelty is predominantly marketed.

The paper introduces a motivational measure of search in the literature and shows that the motivational measure is indeed the proximal measure to other antecedent constructs compared to a behavioral measure of search. Perceived ability to search and perceived value of additional information are shown as important mediators between prior product knowledge and motivation to search.

The objective of this study is to identify, at a macro level, the drivers of store choice in various product categories, in the context of the evolving retail industry in India. The paper attempts to correlate the distinct store features as perceived by respondents with the true motivations of various consumers in patronising various stores. In the process it provides insight as to whether the average Indian consumer values the new store dimensions offered by retailers as a part of the new formats emerging in the market place. The framework evolved for evaluating effectiveness of newer store formats is necessary since it has a major impact on the overall profitability of the retailing business. Suggests that customers in a developing market such as India do not require the service paraphernalia offered by many of the new store formats emerging in the market and notes that this may cast a serious doubt over the retail revolution, which has taken shape in the Indian markets lately. Some hypotheses about the evolution of the retailing business in India, which requires further investigation, are suggested.

International outsourcing has been traditionally looked upon as a low end cost effective servicing option to take advantage of the cost arbitrage that exists across countries. Of late, many outsourcing vendors have realized that the advantages of cost differentials that spurred a lot of the global outsourcing business in the past 20 years will disappear in the medium term. The purpose of this paper is to provide a perspective about how much value addition, besides cost, traditional outsourcing vendors can provide and what may be the facilitator/inhibitors of such activities.

A case describing the setting up of an offshore analytics operation is presented, which gives a backdrop to the challenges faced in relatively high end value creation processes in a remote outsourced (offshore) environment. This provides some empirical support to a proposed model for facilitating the outsourcing of value‐added services.

A model is proposed for determining the degree to which value‐added services can be outsourced. The key dimensions that influence the degree of outsourcing are: the expertise of the vendor; the environmental stability of the offshore domain; the physical barriers to outsourcing complex business processes such as, communication problems and proximity issues; the possibility of knowledge leakage from the outsourcing domain; and the cost benefits of outsourcing.

The paper contends that conventional offshore‐based service vendors may find it difficult to acquire “expert power” and, set aside negative perceptions of “environmental stability” of their domain, in the pursuit to climb up the value chain in their client organizations. The validation of the proposed model is an opportunity for future research.

This paper is one of the first to present a model that will govern the growth of international outsourcing opportunities in high‐end value‐added processes. It also provides some directions for outsourcing vendors to enhance their capabilities over time to leverage this opportunity.