Market Intelligence Research Articles

Integrating business and market intelligence to expedite service responsiveness: evidence from Malaysia

In today’s business world, Malaysian postal and courier companies are rapidly growing due to recent Covid-19 but they face various challenges due to intense competition in the use of high-tech e-services. The paper examines the role of business and market intelligence in expediting service innovation and responsiveness in Malaysia, which is considered the business hub of Asia. Primary survey data were collected from the 93 managerial staff of postal and courier companies in Malaysia. We employed PLS-SEM methodology to test the relationship between the selected variables of interest. The results indicate that market intelligence and business intelligence are the major contributors to service innovation and service responsiveness. Moreover, the role of knowledge management is crucial in better utilization of external and internal knowledge. Finally, this study provides practical guidelines to practitioners and policymakers of postal and courier companies to devise viable strategies for efficiently realizing service innovation and service responsiveness to the best satisfaction of the end customers.

Current state and future development of artificial intelligence in marketing

Artificial intelligence (AI) has emerged as a trend in various industries. In the marketing field, artificial intelligence has been the main driver of its growth and an important tool for companies, organisations, and marketing specialists. However, there is a gap between the existing AI research and the actual application of the technologies in marketing. To bridge the gap, this study focuses on the current state of research on artificial intelligence in marketing and AI technologies used in marketing. Research articles on this topic are searched from the ScienceDirect database and the IEEE Xplore database and the non-empirical studies are filtered out by selection criteria. Then the selected articles are analysed using the method of bibliometrics and content analysis. This study describes the landscape of research in artificial intelligence in marketing, summarises AI technologies applied in the marketing field, provides advice on applying AI applications to marketing for marketing specialists, and presents future research directions for AI specialists. Results show that the application of AI in marketing will increase fast in the coming years. In particular, companies and organisations may greatly benefit from the use of AI technology in marketing to increase sales, cut costs, improve firm productivity, boost innovation, and achieve organisational goals.

Implementation Path of Machine Learning in Intelligent Marketing Scenarios of Commercial Banks

This paper takes commercial banks' intelligent marketing scenario as the entry point and introduces machine learning into the intelligent marketing scenario. It introduces the range of application and implementation path of machine learning in commercial banks' intelligent marketing solutions, discusses the possible problems and methods in the process of model construction, and gives empirical analysis of simulating scenarios. Emphasis is placed on developing effective marketing strategies and adjusting marketing strategies based on the results of model deployment monitoring to establish a complete intelligent marketing system and closed-loop process. It provides reference for commercial banks to improve marketing response rate and realize digital operation.

Does investor sentiment create value for asset pricing? An empirical investigation of the KOSPI‐listed firms

AbstractThis paper proposes the development of an improved investor sentiment index (ISI) to apply on the Korea Composite Stock Price Index (KOSPI) and assess the vitality of sentiment‐based factor for explaining critical equity market anomalies in asset pricing in Korea. We follow the methodology of Huang et al. (2015), the align sentiment index, and employ the partial least squares method to overcome the drawbacks of the pioneering BM index of Baker and Wurgler (2006, 2007). Based on the daily trading and price data for individual companies from 2006 to 2021, we construct a novel ISI, which has robust predicting ability for the aggregate stock market return, in comparison to other popular measures of sentiment in the contemporary finance literature. Furthermore, the sentiment‐based factor in this paper captures the small firm effect that the asset pricing modelling, containing the more topical Fama–French five factor modelling (5F‐FF), has struggled to illuminate completely. Given that our results have shown Korean stock market as fairly well‐organised in terms of the availability of the market intelligence, we speculate our results to have important managerial implications for financial regulators in Korea and countries holding similar economic features.

Correction: Gómez-Prado et al. Product Innovation, Market Intelligence and Pricing Capability as a Competitive Advantage in the International Performance of Startups: Case of Peru. Sustainability 2022, 14, 10703

The authors would like to make the following corrections to the published paper [...]

Entrepreneurship Marketing Development Model To Improve SMEs Economic Performance In Semarang

The empowerment of SMEs (micro small and enterprises) in the midst of globalization and high competition with ASEAN Economic Community (MEA) is expected to be an opportunity to exploit ASEAN regional policy in order to develop market as market player as its market. SMEs (micro small and enterprises) should be able to face various challenges, such as increasing product and service innovation, human resource and technology development, and expanding marketing. Marketing is a fundamental issue for small entrepreneurs. An important aspect of marketer is examined in the context of entrepreneurial efforts to see how marketing theory fits into the practice of entrepreneurship. But in the globalization era with the development of information technology is the essence, it is necessary development of entrepreneurship marketing that is able to reach all consumer in the world, that is through internet marketing or e-commerce. This research seeks to get a model of entrepreneurship marketing development in an effort to improve the performance of MSMEs (micro small and medium enterprises) in Semarang City. The hypothesis is tested using SEM analysis by estimating PLS parameters to assess the outer model and measurement model as well as assess the inner model. Based on the result, development of effective e-commerce has a positive influence on SMEs performance. But, entrepreneur marketing was rejected even though it has a positive influence on E-Commerce Development. This is because of the lack of understanding of the concepts, strategies, methods and market intelligence of the SMEs in Semarang.

Nuclear Family Type Identification Based on Deep Forest Algorithm in Residential Power Consumption

As the fertility rate declines, it becomes increasingly necessary for governments to guide power companies in introducing preferential tariffs to encourage nuclear families to have children. However, traditional household statistics for residential households are time-consuming and insufficient for enterprises seeking to adopt intelligent marketing schemes for different types of households. To address these issues, this paper proposes a nuclear family type identification method for residential electricity consumption based on a deep forest algorithm. The method first classifies nuclear households according to the number of children in them. Then, features are selected by combining the daily 48-point load and prior knowledge of nuclear families. The Pearson correlation coefficient and random forest importance ranking are used to remove features with low correlation and low importance. Additionally, features are classified based on their importance, and the number of features is balanced by stratified sampling to optimize the multi-granularity scan results and improve the model’s generalization. Finally, the improved cascade forest with feature input replacement base learner is trained, and the model is evaluated using accuracy evaluation metrics.The experimental results demonstrate that the proposed model accurately recognizes the number of children in different nuclear families and can be used in power companies to improve lean management. The results show that the improved method is effective in improving recognition com-pared to the original deep forest method, with recognition accuracy 5.1% higher than the random forest method and 0.7% higher than the deep forest method, reaching 94%.

META SYNTHESIS OF STRATEGIC DEVELOPMENT MANAGEMENT BETWEEN INDONESIA AND AUSTRALIA BASED ON CONSTANT MARKET SHARE PERSPECTIVE

The conditions of intense competition in the international market have encouraged Indonesia to be able to compete with other export products from other countries. One of the simple solutions is that the export products that are sold must be of very high quality and take advantage of the empty gaps in the international market. The main way is to fully optimize from viewing and analyzing market strategies. So the nature of our trade will look more offensive to the industrial economy. The use of FTAs is only for reducing tariffs and helping the flow of goods, but Indonesia must also be able to provide encouragement intensively so that these goods can win in one of the FTA areas. The solution presented is directing or piloting starting from one type of export goods. The author observes that the strategy or stages planned with method of meta synthesis. Indonesia are effective in the potential to increase and win Indonesian export products. First, studies by providing solutions on how Indonesian export products can compete and win in one of their destination countries. Second, deepening in the export market shows market power and sends market intelligence to make observations to the micro scale regarding export products and analysis of every policy and solution issued to that country. Third, the overall implementation and application of policy solutions to win Indonesian export products. One of the mistakes made at the implementation stage was said to be exports that were not quite right by Australia.

Challenges and Economic Feasibility of Betelvine Cultivation in Uttar Pradesh

Betel vine (Piper betel L.) is referred to as “Paan” in India. It is the most significant and profitable commercial crop and is cultivated as a significant cash crop due to its high benefit cost ratio (2.3). Fresh betel leaves found rich source of phyto-nutrients and vitamins viz., proteins, minerals, fibre, carbohydrates, vitamin A and vitamin B1. Uttar Pradesh region is favourable for better cultivation of betel vine. There are a few areas in Uttar Pradesh that are well-known for growing betel leaves, such as Bundelkhand, Varanasi, and Unnao. Betel vine farming is labour and capital intensive and best suited to small-scale farmers with a stable source of work and income. The main challenges associated with betel vine cultivation are lack of quality planting material, disease and pest infestation, lack of market, and natural calamities. Leaf rot, wilt, and leaf spot are the major diseases that significantly affect the quality and productivity of betel leaves. But due to its perishable nature and price fluctuations, this is one of the biggest marketing challenges faced by betel vine farmers. Establishing a market intelligence system to forecast prices in advance and simultaneously exploring the export market may be beneficial for realising a higher return on betel vine cultivation. Young farmers are excited to cultivate the betel vine and promote it as a cash crop for gainful employment in Uttar Pradesh. The Government of Uttar Pradesh has launched a scheme to promote the quality production of betel vine leaves.

Assessing PT. Bithouse's Priority Strategy In Achieving The Artificial Intelligence Market

This research paper aims to explore the managerial strategies adopted by PT. Bithouse, an IT consulting company specializing in AI application development, penetrates the artificial intelligence market in Indonesia. The study employs a qualitative research method to gain in-depth insights into the strategic approaches used by PT. Bithouse. Through interviews, observations, and document analysis, the research seeks to provide a comprehensive understanding of the company's management practices, decision-making processes, and adaptation strategies in the rapidly evolving AI landscape. The findings of this research can contribute to the knowledge and understanding of effective managerial strategies for AI-focused companies operating in emerging markets like Indonesia.

ОСОБЕННОСТИ ПРИМЕНЕНИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В МАРКЕТИНГЕ

An example of the use of artificial intelligence in marketing, options for its application for various areas in the marketing strategy are considered

A Nordic Colonial Career Across Borders: Hjalmar Björling in the Dutch East Indies and China

ABSTRACT Building on the latest literature on transimperial mobilities, this article analyses the career of the Finland-Swedish Hjalmar Björling, a merchant and colonial careerist who moved out to the Dutch East Indies around 1870, later also working in assorted roles on the coast of China and in Sumatra’s then-developing plantation economy. He was also an active writer, relaying colonial news and market intelligence as well as accounts of his personal experiences in various Finnish newspapers. This article examines the global, cross-border structures that facilitated Björling’s migration to Southeast Asia and his integration there, arguing that his colonial career sketched out the contours of a pre-existing transnational and specifically Nordic subcircuit of Western imperialism that straddled the boundaries of the Dutch and British empires. Moreover, through his correspondences and ventures, Björling sought to establish himself as an active node in that network connecting northern Europe and maritime Asia. The article argues that a careful consideration of ‘outsider’ experiences like Björling’s challenges conventional, nation-centric understandings of nineteenth-century European empires and helps to uncover the multi-layered systems of mobilities that underpinned their expansion around the world.

Bottlenecks in Nigeria's fresh food supply chain: What is the way forward?

BackgroundNigeria is one of the leading producers of fresh produce, most of which is grown by smallholder farmers. Over 40% of this fresh produce is lost after harvest, resulting in more than 30% loss in smallholders’ income. Scope and approachWe identify the major bottlenecks in Nigeria's fresh food supply chain responsible for the high food losses. We propose possible solutions to mitigate them. Key findings and conclusionsA key bottleneck is that most fresh food produced in the northern region is largely consumed in the south, with the produce traveling long distances through a poor road network. The lack of a continuous cold chain is another key causative factor for food loss. Less than 10% of the fresh food produced passes through a cold chain despite the long distances it needs to travel. There is also limited access to supply chain data and expert market intelligence to assist stakeholders in the decision-making process and process optimizations. To mitigate food losses, smallholder farmers and retailers need better access to clean cooling solutions at affordable prices. This will help them extend produce shelf life and sell produce at attractive market prices by being able to cool their produce. Simple and small-scale passive cooling solutions may also help preserve food for these stakeholders, but are currently rarely used. Furthermore, the available open data needs to be made easily accessible to stakeholders along the fresh supply chain so they can make informed decisions on how best to reduce food losses and maximize profit. Smallholder farmers would also significantly benefit from easier access to expert intelligence on postharvest storage and market information. Providing such expertise via mobile apps can be a powerful tool for remote farmers in a country like Nigeria. Otherwise, it could be difficult to reach them. Nigerian governmental agencies can create the largest gains in the cold chain by implementing policies that support stakeholders financially and improve public-private sector partnerships for rural development.

M&A and Innovation: A New Classification of Patents

Policymakers are increasingly concerned that incumbent acquisitions of small or young firms may slow down rather than speed up innovation, but it is difficult to identify which firms are related in the fast-changing space of technological innovation. This paper proposes a new, data-driven method to classify patent data into tech-business zones on a probabilistic basis, using patent assignee information. After combining mergers and acquisitions data from S&P Global Market Intelligence with PatentsView data from the US Patent and Trademark Office, we discuss how the zone classification can aid merger reviews and other lines of research.

Automatic Clustering and Fuzzy Logical Relationship to Predict the Volume of Indonesia Natural Rubber Export

Natural rubber is one of the pillars of Indonesia's export commodities. However, over the last few years, the export value of natural rubber has decreased due to an oversupply of this commodity in the global market. To overcome this problem, it is possible to predict the volume of Indonesia natural rubber exports. Predicted values can also help the government to compile market intelligence for natural rubber commodities periodically. In this study, the prediction of the export volume of natural rubber was carried out using the Automatic Clustering as an interval maker in the Fuzzy Time Series or usually called Automatic Clustering and Fuzzy Logical Relationship (ACFLR). The data used is 51 data per year from 1970 to 2020. The purpose of this study is to predict the volume of Indonesia natural rubber exports and compare the prediction results between the Automatic Clustering and Fuzzy Logical Relationship (ACFLR) and Chen's Fuzzy Time Series. The results showed that there was a significant difference between the two methods, ACFLR got 0.5316% MAPE with and Chen's Fuzzy Time Series model got 8.009%. Show that the ACFLR method performs better than the pure Fuzzy Time Series in predicting volume of Indonesia natural rubber exports.

Entrepreneurial orientation and new product performance in SMEs: The mediating role of customer participation

Entrepreneurially oriented SMEs are known to network to overcome resource limitations regarding newness and smallness, thus market intelligence acquisition and utilization have been shown to be of importance for EO firms. This study examines the mediating role of customer participation in new product development (NPD) on the relationship between entrepreneurial orientation (EO) and NPD performance. In a study of 232 SMEs, the results show that EO is positively related to customer participation and customer participation mediates the relationship between EO and NPD performance. Two contingency factors are examined that impact EO’s relationship with customer participation – firm age and firm size. The results show that when firms become older or larger, customers become less utilized in EO firms’ NPD process, thus indirectly affecting the impact of EO on NPD performance negatively.

Tracking Online Interest in Artificial Intelligence in Ophthalmology Using Google Trends

ABSTRACT Purpose To examine trends in internet search queries related to artificial intelligence (AI) in ophthalmology and determine the correlation between online interest in AI, capital investment in AI, and peer-reviewed indexed publications regarding AI and ophthalmology. Methods Online search trends for “AI retina”, “AI eye”, and “AI healthcare” were obtained via Google Trends from 2016 to 2022 on a relative interest scale in 1-week intervals. Global venture financing of AI- and machine learning (ML)-focused companies in healthcare was tracked from 2010 to 2019 from the consulting company, Klynveld Peat Marwick Goerdeler (KPMG), and the technology market intelligence company, CB Insights. Citation count from pubmed.gov was determined using the search query “artificial intelligence retina” from 2012 to 2021. Results An increasingly linear growth in online search trends for “AI retina”, “AI eye”, and “AI healthcare” keyword searches was observed between 2016 and 2022. Global venture financing of AI and ML companies in healthcare also increased exponentially over the same time frame. There was an exponential increase in citations with nearly a 10-fold increase as reported by PubMed from 2015 onwards for the “artificial intelligence retina” search query. There was a significant and positive correlation between online search trends and investment trends (correlation coefficients of 0.98–0.99 and p-values <0.05) and between online search trends and citation count trends (correlation coefficients of 0.98–0.99 and p-values <0.05). Conclusions These results demonstrate that the applications of AI and ML in ophthalmology are increasingly being investigated, financed, and formally researched, suggesting a prominent role for AI-derived tools in ophthalmology clinical practice in the near future.

Changing Treatment Trends for MS Patients Recently Initiated on Their First DMT (P12-3.012)

<h3>Objective:</h3> To evaluate if disease-modify therapy (DMT) choice has changed for treatment-naïve multiple sclerosis (MS) patients from 2020–2022. <h3>Background:</h3> Cross-sectional audit of MS patients was conducted annually. Data were reviewed by an independent market intelligence agency which specializes in tracking the neurology market. <h3>Design/Methods:</h3> US neurologists (2020: N=199; 2021: N=205; 2022: N=208) completed a survey and contributed chart reviews for a retrospective, cross-sectional audit on MS patients who started their first DMT within the prior 3 months (2020: N=1,006; 2021: N=1,018; 2022: N=1,095). MS patients were analysed as a whole, as well as by physician-reported MS subtypes for relapsing-remitting MS (RRMS; N=722, N=768, N=827), active secondary progressive MS (aSPMS; N=74, N=50, N=59), and primary progressive MS (PPMS; N=92, N=69, N=72). <h3>Results:</h3> Overall use of glatiramer acetate (GA) (32% in 2020, 16% in 2022) has declined; use of fumarate agents (13%, 21%) and anti-CD20 monoclonal antibody (mAb) DMTs (13%, 21%) expanded. Interferon (13% in 2020 and 2022) and S1P receptor modulator class (12%, 14%) use has remained stable. Use of both brand (18%, 11%) and generics (14%, 6%) of GA declined. For fumarates, use has shifted from branded dimethyl fumarate (DMF; 13%, 8%) to generic DMF (0%, 6%) and diroximel fumarate (0%, 6%). For S1Ps, use has shifted from fingolimod (10%, 6%) to ozanimod (0%, 4%) and ponesimod (0%, 1%). Changes in DMT use are similar for RRMS: GA use declined (31%, 16%); fumarates (17%, 23%) and anti-CD20 mAb DMT (9%, 19%) use expanded. GA use also declined for aSPMS (30%, 7%) and PPMS (30%, 8%); anti-CD20 mAb DMT use grew for aSPMS (19%, 41%). <h3>Conclusions:</h3> DMT prescribing trends are evolving for MS patients recently initiated on their first DMT. Use of GA agents has fallen across MS subtypes, while use of the high-efficacy anti-CD20 mAb DMT class has expanded. <b>Disclosure:</b> Dr. McFadden has nothing to disclose.

Effects of the anthropomorphic image of intelligent customer service avatars on consumers' willingness to interact after service failures

PurposeIntelligent customer service has started replacing human employees in providing services to customers in numerous industries. Based on the expectancy disconfirmation theory, this study explores how different types of anthropomorphic avatar images of the intelligent customer service would affect consumer responses such as the willingness to interact, in the context of a service failure. The underlying mechanism and boundary conditions are also examined.Design/methodology/approachTwo experimental studies were conducted to investigate the effect of the anthropomorphic image of intelligent customer service on consumers' willingness to interact and the potential role of consumer expectation and disappointment, following a service failure (Study 1). The moderating effect of anthropomorphic type was also explored (Study 2).FindingsIn the context of a customer service failure, an anthropomorphized intelligent customer service avatar that appeared competent (vs. warm) induced higher customer disappointment. However, if the anthropomorphic avatar had a cartoon-like appearance, the effect of avatar image perception (competent vs. warm) on consumers' willingness to interact diminishes.Originality/valueThis research enriches and expands the literature on interactive marketing and artificial intelligence and provides practical guidance for companies to design or choose avatar images for intelligent customer service.

The impact of customer-focus on the performance of business organizations: evidence from SMEs in an emerging West African economy

PurposeThe purpose of this paper is to investigate the impact of customer-focus on small medium enterprise (SME) performance from the perspective of a resource-based view (RBV).Design/methodology/approachThis research study implemented a survey strategy to gather data from 255 respondents on the registered list of Ghana Enterprise Agency (GEA) in the eastern region of Ghana. Scales used to gather data were operationalized from previous research studies. A structural equation modeling (SEM) path analysis was used to estimate the impact of customer-focus on the performance of SMEs.FindingsThe outcomes of this study indicate that customer-focus has a significant positive impact on SME performance, hence backing the current demand for investigating the distinct influence of customer-focus on SME performance. The results show that customer-focus has a positive and significant relationship with financial performance, customer performance, internal business process performance and learning and growth performance, thus supporting the literature on the positive impact of customer-focus on SME performance. Therefore, customer-focus determinants used in this study, including co-creation, networking ties, customer insight and artificial intelligence marketing (AIM), are critical to the optimization of SME performance.Research limitations/implicationsNotwithstanding the importance of this research study mentioned earlier, the study has limitations. Notably, the sample size of this study can be increased to capture SME respondents in other geographical zones that were not included in this study. Future research studies may address how business environment conditions moderate the relationship between customer focus and performance, and also the cause-effect of the relationship between customer focus and business environment conditions on SME performance.Practical implicationsThe practical implications consist of two main items. First, this study empowers SME owners and managers to develop a customer focus technique as a central strategic goal in their quest for SME performance optimization. Second, SME owners and managers should progressively exploit the four determinants of customer focus which include co-creation, networking ties, customer insight and (AIM in order to accrue important resources for effective utilization of their customer focus competences as a way to enhance their performance.Social implicationsThis study is targeted at the sound development of SMEs to bring about poverty alleviation and employment. Poverty, unemployment and poor living standards are recognized as vital social challenges in most emerging economies. The establishment of customer focus as an important strategic capability provides opportunities for SME survival, profitability and growth.Originality/valueGenerally, the findings of this research study provide a strong backing to RBV perspective and the proposition that customer-focus and its determinants (i.e. co-creation, networking ties, customer insight and AIM) should be acknowledged as a vital strategic resource for optimizing the performance of SMEs. This research study also provides new knowledge contribution to the present body of knowledge on customer-focus orientation and management literature, particularly in the context of an emerging economy.