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Market intelligence is a cornerstone of the marketing concept and essential to market-focused strategic planning and implementation. Although the importance of market intelligence is widely accepted, how managers can ensure the organization-wide generation, dissemination, and responsiveness to market intelligence remains a persistent challenge. In this article, the authors investigate market intelligence dissemination practices and their resulting managerial responses. Using qualitative methods, the authors identify five market intelligence dissemination practices that either update and reinforce organization members' existing schemas (mental models) of the market or create new, shared schemas of the market. Specifically, they find that the creation, existence, or absence of organizationally shared market schemas is crucial in explaining the effectiveness of different market intelligence dissemination practices. Thus, in addition to being experts on market intelligence, intelligence directors must be authorities on organizational learning and ways to create shared meaning structures that enable disseminated intelligence to be understood and used within their organizations. The authors conclude with suggestions for practitioners on how to manage intelligence dissemination across their organizations more effectively and efficiently. [ABSTRACT FROM AUTHOR]

Addressing the challenge of aligning how market research is practiced and how it is taught has been a recurrent theme in the marketing education literature. Recently, the growth of digital marketing and new forms of customer data have disrupted many traditional aspects of marketing practice. Companies are increasingly able to collect data directly from their customers, via large technology firms or from specialist data providers. This has reduced the demand for the traditional fieldwork-based data collection that remains a core focus within the market research curricula. This article considers the past, present, and future role of market research education in the light of the changing practitioner environment. An audit of market research courses is carried out, weaknesses identified, and suggestions made to better align market research courses with evolving skills requirements. More broadly, the article challenges educators to evaluate the extent to which the marketing curriculum can respond to the disruptions brought by the emerging digital economy. [ABSTRACT FROM AUTHOR]

When it comes to new technologies, I have never really been an “early adopter.” “Reluctant latecomer” would be closer to the mark, for my mantra has always been that “if it isn’t broken, don’t fix it.” I still prefer LPs to MP3s, DVDs to streaming, and paper copies of journals, books, and magazines to their online equivalents. I have never tweeted, never used Facebook, and only recently (and with grave misgivings) acquired a smartphone. More to the point, my cars have manual keys, manual transmissions, and manual GPS (i.e., road atlases). Several decades into the digital age, I remain a comfortably analog person. [ABSTRACT FROM AUTHOR]

There are increasing international efforts to tackle climate change by reducing the emission of greenhouse gases. As such, the use of electrolytic hydrogen as an energy carrier in decentralised and centralised energy systems, and as a secondary energy carrier for a variety of applications, is projected to grow. Required green hydrogen can be obtained via water electrolysis using the surplus of renewable energy during low electricity demand periods. Electrolysis systems with alkaline and polymer electrolyte membrane (PEM) technology are commercially available in different performance classes. The less mature solid oxide electrolysis cell (SOEC) promises higher efficiencies, as well as co-electrolysis and reversibility functions. This work uses a bottom-up approach to develop a viable business model for a SOEC-based venture. The broader electrolysis market is analysed first, including conventional and emerging market segments. A further opportunity analysis ranks these segments in terms of business attractiveness. Subsequently, the current state and structure of the global electrolyser industry are reviewed, and a ten-year outlook is provided. Key industry players are identified and profiled, after which the major industry and competitor trends are summarised. Based on the outcomes of the previous assessments, a favourable business case is generated and used to develop the business model proposal. The main findings suggest that grid services are the most attractive business sector, followed by refineries and power-to-liquid processes. SOEC technology is particularly promising due to its co-electrolysis capabilities within the methanol production process. Consequently, an “engineering firm and operator” business model for a power-to-methanol plant is considered the most viable option.

IntroductionEpilepsy is a neurological disease that can negatively impact a person’s physical, psychological, social, and emotional well-being. The aim of this study was to provide insights into the experiences of people with epilepsy on polytherapy (i.e., people on a combination of two or more anti-seizure medications [ASMs]), with an emphasis on their emotional journey.MethodsMarket research was conducted with 40 people with epilepsy from France, Germany, Italy, Spain, and the United Kingdom. Semi-structured interviews were analyzed using both a content and framework analysis approach. A content analysis of participants’ expressed emotions was used to illustrate the changes of emotions experienced by people with epilepsy from presentation through to monitoring and follow-up stages.ResultsIn each stage of the journey, themes and subthemes were identified under the overarching headings: Stage 1: Presentation – Life is turned upside down; Stage 2: Diagnosis – Period of learning; Stage 3: Treatment – Aspirations and experimentation; and Stage 4: Monitoring and follow-up – Feeling “out on a limb”. The research identified key unmet needs and opportunities for people with epilepsy to improve their subjective experiences at different stages of their disease journey, namely: (1) establish and promote support networks from presentation through to monitoring and follow-up stages; (2) accelerate pathway to diagnosis; (3) provide opportunities to discuss the diagnosis with patients; (4) clarify treatment-change guidelines for patients; and (5) develop a shared treatment decision-making/empowerment tool.DiscussionThe research findings and recommendations have the potential to drive change at an individual level, as well as at a healthcare level.

Drinking straws have been almost a staple commodity and a hygiene tool to customers buying drinks and beverages from expensive iced coffee sold in coffee shops down to bottled soft drinks sold in retail stores. As for the continuous usage of plastic drinking straws, so is the continuous generation of solid waste. Furthermore, petroleum is needed for the production of plastic drinking straws, hence another cause of air pollution. The paper tackles the possibility of introducing in the market, a drinking straw made of dried mango leaves. Dried Mango leaves are another solid waste being discarded on a regular basis in many places in the Philippines. Thus, lessening the combustion of the said leaves would decrease the worsening greenhouse effect. To ensure the sustainability of the utilization of this innovative product, a market study is conducted. The different micro, small and medium enterprises where consumers buy drinking straws in the province of Pampanga were surveyed as target market. A demand-supply gap analysis is presented which in the end, leads to the conclusion of the projected number of unsatisfied customers from existing consumers of drinking straw made of plastic. [ABSTRACT FROM AUTHOR]

There is a dearth of knowledge regarding the consumption habits of street foods, despite the fact that individuals in low- and middle-income nations rely heavily on SF for their diet. An online survey employing a structured questionnaire was used to perform a cross-sectional study on 200 street food consumers in the Prayagraj/Allahabad District. Customers were approached and requested to participate who went to the randomly sampled Street Foods vendors and stores. The majority of consumers were male, between the ages of, and had at least a 10+2 and a Bachelor's degree. The primary findings showed that 91.5% of these consumers virtually always ate street food. In Prayagraj/Allahabad District, the most frequently consumed items were various types of street food products. chaat, bun, samosa, kachauri/khasta, fritters, south and north Indian chow mein, non-vegetarian, eggs, and dried goods. Consumers answered that they would prefer to buy healthier street foods (91.5%) if they were accessible. In the Prayagraj/Allahabad District, there is a sizable market for consumers of street food. Although street food is the majority of what is eaten, if healthier options are offered, people would be eager to buy them. [ABSTRACT FROM AUTHOR]

Objective: To identify potential mango products, as an alternative to take advantage of mango production that is not commercialized in the southern zone of Sinaloa. Methodology: Tow stages were implemented: (1) Generation of product alternatives. (2) Selection of a product. Results: In Stage 1, filled cookie, ate and bar were identified for their ease of purchase, functional content, and natural ingredients, with bar being the product with the greatest potential for success. In Stage 2, bars in amaranth, mixed nuts and chocolate and mixed cereal and yogurt presentations were the most preferred. Limitations: May be the identification of attributes through surveys can be subjective, so sensory testing with consumers is recommended. Conclusions: The three potential products and their attributes identified were: (1) mixed nuts and chocolate bar was preferred because of its energy contribution, ease of purchase and natural ingredients; (2) amaranth bar was preferred because of its protein, carbohydrates, fiber, natural ingredients, and price; and (3) mixed nuts and chocolate bar was preferred because of its protein, carbohydrates, fiber, natural ingredients, and price. Finally, (3) Cereal mix bar with yogurt was preferred for its meal replacement, fiber content and contribution to health. [ABSTRACT FROM AUTHOR]

Digitally dependent firms, which are linked to a large number of other firms with varying capabilities, are challenged on evaluating networks with which to engage. Empirically supported heuristic guidance can aid firms in identifying alliances to strengthen capability. We report a case study of firms linked to the Internet of Things (IoT) with a broad view of firms that leverage digital technologies to offer a diverse range of next generation consumer and industrial products and services. This article includes a network analysis of their publicly declared deals to reveal clusters of high volume deals-making activity and their respective hub firms. Based on the rationale of deals of the hub firms, the firms are categorized in a perceptual framework of market-oriented versus technology-seeking inclination. The inclinations of these hub firms were found to vary between technology-seeking, market-oriented, and ambidextrous. The results of this article can inform hub firms in assessing investment portfolios, nonhub firms in evaluating networks governed by hub firms, and policy makers to design incentives for digital adoption. [ABSTRACT FROM AUTHOR]

This article characterized the linear trends and interannual signals of terrestrial water storage (TWS) and meteorological variables including precipitation (P) and evapotranspiration (ET) over the arid Northwestern China (NWC). The relative impaction of P, ET, and human water utilization (HU) on TWS variation among the 10 watersheds of NWC (i.e., 5 watersheds in Xinjiang, 3 watersheds in Hexi Corridor, and 2 watersheds in Qinghai) were then investigated. The result indicated that groundwater storage (GWS) was the main contributor to the TWS variation and matched well with TWS in spatial features or watershed-scale variations. The entire NWC presented growth trends for P (0.05 cm/year) and ET (0.22 cm/year) and decline trends for TWS (−0.19 cm/year) and GWS (−0.20 cm/year). The watersheds in Qinghai province where mainly affected by natural factors showed the increasing TWS/GWS trend. The watersheds in Xinjiang and Hexi Corridor, which had strong impact from human activities generally showed the declining TWS/GWS trends, but Xinjiang showed more intensive declining trend than Hexi Corridor. The analysis of HU indicated that water sustainable management and water-saving technologies had effectively kept down the tendency of TWS/GWS declining in the watersheds in Hexi Corridor, however, they were not sufficient to address the water shortage caused by farmland expansion, slight P growth, and high ET growth in Xinjiang. Groundwater use, as the main source to compensate for the increase in HU (especially agricultural water use), exacerbated TWS/GWS loss in Xinjiang. This article provides valuable information for the water management over the arid NWC. [ABSTRACT FROM AUTHOR]

Sentiment analysis as a field has come a long way since it was first introduced as a task nearly 20 years ago. It has widespread commercial applications in various domains like marketing, risk management, market research, and politics, to name a few. Given its saturation in specific subtasks — such as sentiment polarity classification — and datasets, there is an underlying perception that this field has reached its maturity. In this article, we discuss this perception by pointing out the shortcomings and under-explored, yet key aspects of this field necessary to attain true sentiment understanding. We analyze the significant leaps responsible for its current relevance. Further, we attempt to chart a possible course for this field that covers many overlooked and unanswered questions. [ABSTRACT FROM AUTHOR]

Copyright of Tesla Revista Científica is the property of Puerto Madero Editorial Academica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Medien & Kommunikationswissenschaft is the property of Nomos Verlagsgesellschaft mbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The accurate prediction of the remaining useful life (RUL) of lithium-ion batteries (LIBs) is a key, challenging research direction. In this study, a battery degradation model is built based on the LIB dataset of NASA. A data decomposition prediction method, which extracts the linear trend from the capacity degradation data and then predicts the residuals of time series with nonlinear relations, is proposed. Then, an autoregressive integrated moving average-long short-term memory (ARIMA-LSTM) combined model for predicting the RUL of LIBs is established. The linear trend of capacity degradation is predicted by the ARIMA model and the LSTM model is established to predict the nonlinear residuals separated from the capacity degradation. The summation of both obtains the final battery RUL prediction result. Compared with the LSTM model and prediction models of similar types in existing literature in recent two years, the experimental results show that the RUL prediction error of the proposed model in this article is no more than one cycle, which is smaller than that of all the models involved in the comparison. Thus, this method has higher prediction accuracy and model generalization ability in the prediction of the remaining useful life of LIBs. [ABSTRACT FROM AUTHOR]

WiFi sensing has received recent and significant interest from academia, industry, healthcare professionals, and other caregivers (including family members) as a potential mechanism to monitor our aging population at a distance without deploying devices on users’ bodies. In particular, these methods have the potential to detect critical events such as falls, sleep disturbances, wandering behavior, respiratory disorders, and abnormal cardiac activity experienced by vulnerable people. The interest in such WiFi-based sensing systems arises from practical advantages including its ease of operation indoors as well as ready compliance from monitored individuals. Unlike other sensing methods, such as wearables, camera-based imaging, and acoustic-based solutions, WiFi technology is easy to implement and unobtrusive. This paper reviews the current state-of-the-art research on collecting and analyzing channel state information extracted using ubiquitous WiFi signals, describing a range of healthcare applications and identifying a series of open research challenges, including untapped areas of research and related trends. This work aims to provide an overarching view in understanding the technology and discusses its use-cases from a perspective that considers hardware, advanced signal processing, and data acquisition. [ABSTRACT FROM AUTHOR]

This article gives a scientometric analysis of research advances in mobility-on-demand (MoD)systems. By reviewing 191 articles with diverse perspectives from the past 10 years, a scientometric study is conducted using CiteSpace, giving an integrated knowledge mind mapping of MoD systems. The results indicate that the major contributions in MoD systems field are mainly from the United States, Singapore, China, and Germany. Meanwhile, pivotal institutions, journals, and article keywords are discussed. MoD system knowledge domains are concentrated in the categories of demand and service, system optimization, impacts and factors, and response and choice. The development of MoD systems is evolving from taxis and minibuses to autonomous vehicles. In particular, research interest in autonomous MoD systems is rapidly growing. This analysis gives a comprehensive and integral knowledge mind mapping, which contributes to the MoD system information network and provides valuable insights into future research directions and developments for investigators and software developers in the field of vehicle-sharing and traffic scheduling. [ABSTRACT FROM AUTHOR]

Although thermal infrared imaging has been developed as an important tool of remote sensing rock mechanics (RSRM) since the 1990s, the relationship between infrared emissivity and rock fragments, which is essential for interpreting positive infrared abnormity, has not been investigated. In this letter, the infrared brightness temperature (IBT) ($T_{b}$) of sandstone, marble, and granite, including an intact rock specimen and its fragments of six-level sizes, was experimentally detected with an infrared imaging system indoor. The relationship between the detected $T_{b}$ and the measured size of rock fragments is investigated, and the equivalent emissivity $\varepsilon _{\!\!f}$ of rock fragments of different sizes is obtained. It was discovered that $\varepsilon _{\!\!f}$ of rock fragments rose up to 8.43% compared to that of intact rock and behaved the maximum as the fragment sizes get close to the mineral particle scale (MPS) of the rock. $T_{b}$ is hence locally lifted by 6.16 K. This letter revealed that the rise of $\varepsilon _{\!\!f}$ is a third remote sensing mechanism, besides the known thermoelastic and friction thermal effects, of local $T_{b}$ enhancement in process of rock loaded to fracturing, which provides new experimental supports to infrared imaging detection on rock fracturing and IBT-based stability analysis in rock engineering and geostructures. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the article is to try to answer the question which of the social policy instruments can convince the society to adopt transport solutions based on the concept of electromobility to the greatest extent. Design/methodology/approach: The considerations are social research, a research experiment in the form of a method (CAWI) was used, which was used to verify the role of selected instruments in the process of the announced transformation of social mobility. In the research area, the focus was on the assessment of possible changes in shopping preferences and transport mobility in terms of selected social policy instruments. Economic, legal and informational instruments were analysed. Findings: The author indicates that the process of managing the development of electromobility should be implemented with the help of properly selected social policy instruments and go hand in hand with the changes taking place within an increasingly aware society. Research limitations/implications: The presented survey research was carried out on a specific research sample of approximately 1,000 respondents. Certainly, in the near future there will be a need for much broader analyzes and research, in particular with regard to changes in the income of citizens, planned reforms of social programs and projected increases in the prices of energy resources. Practical implications: The research results are the first approach to indicate to the government administration which social policy tools have the greatest impact on the process of managing the development of electromobility in Poland. Social implications: Research shows that there are links between economic, social and environmental issues in the management of the electromobility development process in Poland. Originality/value: The experimental research approach may be helpful in assessing the effectiveness of the implications of selected social policy instruments in the management of the electromobility development process in Poland. [ABSTRACT FROM AUTHOR]

Due to their increasing complexity, today’s software systems are frequently built by leveraging reusable code in the form of libraries and packages. Software ecosystems (e.g., npm) are the primary enablers of this code reuse, providing developers with a platform to share their own and use others’ code. These ecosystems evolve rapidly: developers add new packages every day to solve new problems or provide alternative solutions, causing obsolete packages to decline in their importance to the community. Developers should avoid depending on packages in decline, as these packages are reused less over time and may become less frequently maintained. However, current popularity metrics (e.g., Stars, and Downloads) are not fit to provide this information to developers because their semantics do not aptly capture shifts in the community interest. In this article, we propose a scalable approach that uses the package’s centrality in the ecosystem to identify packages in decline. We evaluate our approach with the npm ecosystem and show that the trends of centrality over time can correctly distinguish packages in decline with an ROC–AUC of 0.9. The approach can capture 87% of the packages in decline, on average 18 months before the trend is shown in currently used package popularity metrics. We implement this approach in a tool that can be used to augment the npms metrics and help developers avoid packages in decline when reusing packages from npm. [ABSTRACT FROM AUTHOR]

Technology evaluation is one of the most essential tasks for today's companies to make correct decisions that will increase their competitiveness. To date, numeroushave been made to address technology evaluation in the literature. Nevertheless, none of them have built a technology map or classified technologies based on their effects on the competitive power of a company in practice. To overcome the limitations of previous studies, a regression-based patent data analysis is proposed here for technology evaluation in this article. To this end, the proposed approach builds a technology map and classifies the technologies into four classes with respect to the technology effect ratio, namely 1) very high effect class, 2) high effect class, 3) medium effect class, and 4) low effect class. The technology evaluation of weapon technology in the defense industry has been conducted to show how the proposed approach works in real life. A good technology management strategy can be selected among available alternatives by decision makers and managers using the proposed approach. The results show that the proposed technology evaluation process can be used effectively in practice. [ABSTRACT FROM AUTHOR]

Crowdsourcing is a multidisciplinary research area that represents a rapidly expanding field where new applications are constantly emerging. Research in this area has investigated its use for citizen science in data gathering for research and crowdsourcing for industrial innovation. Previous studies have reviewed and categorized crowdsourcing research using qualitative methods. This has led to the limited coverage of the entire field, using smaller discrete parts of the literature and mostly reviewing the industrial aspects of crowdsourcing. This study uses a scientometric analysis of 7059 publications over the period 2006–2019 to map crowdsourcing research to identify clusters and applications. Our results are the first in the literature to map crowdsourcing research holistically. In this article, we classify its usage in the three domains of innovation, engineering, and science, where 11 categories and 26 subcategories are further developed. The results of this article reveal that the most active scientific clusters where crowdsourcing is used are environmental sciences and ecology. For the engineering domain, it is computer science, telecommunication, and operations research. In innovation, idea crowdsourcing, crowdfunding, and crowd creation are the most frequent areas. The findings of this study map crowdsourcing usage across different fields and illustrate emerging crowdsourcing applications. [ABSTRACT FROM AUTHOR]

The relevance of microgravity research—i.e., research activities related to the possibility to generate and/or take advantage of an environment scantly affected by gravitational effects—is becoming more and more important for both policymakers and executives, not only in the aerospace domain but also in many other domains. However, tracing the evolution of the technological landscape deriving from microgravity research is very complex due to the fast-growing solutions emerging from such a research activity as well as their diversified nature in terms of actors and domains of relevance. This makes difficult to identify/foresee the most exploited/promising solutions related to microgravity research, set the research budget for subsequent R&D activities, recognize relevant business opportunities, and regulate access to space. Therefore, this article aims to delve into the technological outcomes of microgravity research, so revealing their main development trends (i.e., temporal trends, the geographic origins of related solutions, main technological areas, key research organizations, and the highly impacting technologies) to provide visions of the future (i.e., technology foresight) and derive implications for business and policy. To do so, we collected and analyzed a unique sample of 4401 patents, applied between 1960 and 2020, in the wide domain of microgravity research. [ABSTRACT FROM AUTHOR]

Identifying the development trends of emerging technologies with disruptive potential as early as possible is crucial for enterprise research and development (R&D) investment planning and government R&D strategic planning. Many researchers have used academic papers and patent data to identify trends in emerging technologies, although they rarely have made use of web news data focused on emerging technologies. Web news contains a large amount of social awareness data that represents the public's sense of and response to emerging technologies, and the social awareness data is of great significance for identifying the development trends of emerging technologies. Therefore, this article presented a research framework to identify the development trends of emerging technologies using patent analysis and web news data mining. In the research framework, first, we have used patent analysis to analyze the evolution topics of these emerging technologies, and have applied the topic model to study the changing patterns of publics’ topics of concern regarding emerging technologies contained in web news. Second, we have made a comparison analysis of the results of patent analysis and the public’ sense of and response to emerging technologies contained in web news. Then, we have applied an improved sentiment analysis to study the changing patterns of publics’ expectations for emerging technologies contained in web news. Finally, by studying the changes in publics’ topics of concern and publics’ expectations for emerging technologies over time, we have identified the development trends of emerging technologies. The perovskite solar cells technology is used as a case study to analyze the effectiveness and feasibility of the framework. This article provides a new research perspective to identify technology trends, and contribute to the technology forecasting methodology. [ABSTRACT FROM AUTHOR]

This article used nine patent value indicators to compare the differences in the characteristics of U.S. patents for which provisional applications (PAs) were submitted and other patents without PAs (NPAs). The findings revealed significant differences in the average numbers of backward and forward citations, patent and nonpatent references, and patent claims, patent family size (number of patents and number of countries), and duration of examination between the two groups of patents granted between 2005 and 2017 by United States Patent and Trademark Office. Increasing trends were observed in the average number of backward citations and average percentage of patents renewed per year in both PA and NPA groups, whereas decreasing trends were observed in the average numbers of forward citations, countries, claims, and average duration of examination per patent and per year in PA and NPA groups. Differences in patent characteristics based on type and field were observed. This article also revealed more significant differences in PAs than in NPAs because of a larger number of pairs of fields. The results of this study confirmed that PAs have a stronger association with patent value and provided further justification for filing PAs, in addition to obtaining an early effective date for new inventions. [ABSTRACT FROM AUTHOR]