Sensory Profiling and External Preference Mapping of Pre-Thickened Water Products for Dysphagia

Dysphagia is a dysfunction of the swallowing system and thickened beverages are widely prescribed as a treatment. The objective of this study was to determine the sensory characteristics of pre-thickened water products and determine sensory drivers of liking for those types of products. Pre-thickened water products (two starch-based and two gum-based) were tested in both nectar and honey thick versions. Based on product availability, one product was neutral water, and the others were water with lemon flavoring added. The sensory characteristics of the products were evaluated with a highly trained descriptive panel, and the viscosity of the products was evaluated with both the Bostwick consistometer and the line spread test. Previously published consumer data was used to determine preference maps with the descriptive data. All lemon-flavored products had similar flavor characteristics, except the Thick & Easy Clear that had a less lemon-related flavor than the others. After excluding the lemon-related flavor characteristics, all pre-thickened products had similar “base flavor” notes, no matter whether the products were starch-based or gum-based. This contrasts with literature, which reports differences in flavor of thickened beverages prepared using thickening agents. The thickness of the products varied between nectar and honey thickness, but also varied among products that were stated to be at the same level of thickness. External preference mapping showed that both lemon-related flavor and a thinner beverage texture are potential drivers of consumers acceptance of the product, which was expected based on other studies. In conclusion, pre-thickened beverages are good alternatives for self-mixed thickening agents but a standard for thickness should be agreed on and used by manufacturers.

Assesing the Merger of Online Platform Companies: Does it Lead to Monopoly or just Business Expansion? (Analysis of The Merged Company of GoTo)

Two large digital platform companies, Gojek and Tokopedia, officially merged to form a holding company called the GoTo Group that is considered to have anti-competitive behavior and potentially data monopoly. This article aimed to analyze the adequate response to potential violations of the Prohibition of Monopolistic Practices and Unfair Business Competition Regulation and legal issues related to consumer data monopoly issues. This article uses normative legal research with the conceptual research and statute approach. The result shows that it is necessary to define “relevant markets” and the “substituted products” to determine the existence of unfair business competition in the Gojek-Tokopedia merger. It requires analyzing the consumer behavior in other marketplaces other than Tokopedia; when consumers do not "run" to Gojek, it means they are not in the same market. To prevent privacy protection failures in post-merger data integration, companies need to assess data sharing that may be carried out as part of a risk assessment. Regarding the rights of data subjects, The company needs to provide notification to the data subject regarding the Merger and Acquisition (M & A) given the data subject's right to refuse and guarantee that the M & A process will not violate the right to privacy of the customer's dataKeywords: Competition Law; Digital Platform; Merger Menilai Penggabungan Perusahaan Platform Online: Apakah Mengakibatkan Monopoli atau Hanya Ekspansi Bisnis? (Analisis Penggabungan GoTo)AbstrakDua perusahaan platform digital besar, Gojek dan Tokopedia, resmi bergabung membentuk holding company bernama GoTo Group yang dinilai memiliki perilaku anti persaingan dan berpotensi monopoli data. Artikel ini bertujuan untuk menganalisis respon yang memadai terhadap potensi pelanggaran Peraturan Larangan Praktik Monopoli dan Persaingan Usaha Tidak Sehat serta masalah hukum terkait masalah monopoli data konsumen. Artikel ini menggunakan penelitian hukum normatif dengan pendekatan penelitian konseptual dan undang-undang. Hasil penelitian menunjukkan perlunya mendefinisikan “pasar relevan” dan “produk substitusi” untuk mengetahui adanya persaingan usaha tidak sehat dalam merger Gojek-Tokopedia. Hal ini membutuhkan analisis perilaku konsumen di pasar lain selain Tokopedia; ketika konsumen tidak “lari” ke Gojek, berarti mereka tidak berada di pasar yang sama. Untuk mencegah kegagalan perlindungan privasi dalam integrasi data pasca-merger, perusahaan perlu menilai pembagian data yang mungkin dilakukan sebagai bagian dari penilaian risiko. Mengenai hak subjek data, Perusahaan perlu memberikan pemberitahuan kepada subjek data mengenai Merger dan Akuisisi (M&A) mengingat hak subjek data untuk menolak dan menjamin bahwa proses M&A tidak akan melanggar hak privasi data pelangganKata Kunci: Hukum Persaingan Usaha; Platform Digital; PenggabunganОценка слияний компаний онлайн-платформ: приведет ли это к монополии или просто к расширению бизнеса? (Анализ слияний GoTo (Gojek и Tokopedia) АннотацияДве крупные компании, занимающиеся цифровыми платформами, Gojek и Tokopedia, официально объединили свои усилия, чтобы сформировать холдинговую компанию GoTo Group, которая, как считается, ведет антиконкурентную политику и может монополизировать данные. Данная статья направлена на анализ адекватного реагирования на возможные нарушения Положения о запрещении монополистической практики и недобросовестной конкуренции, а также на правовые вопросы, связанные с проблемой монополии на данные потребителей. В данной статье используется нормативно-правовое исследование с концептуальным и правовым исследовательским подходом. Результаты исследования указывают на необходимость определить «соответствующие рынки» и «продукты-заменители», чтобы определить наличие недобросовестной деловой конкуренции в слиянии Gojek-Tokopedia. Это требует анализа поведения потребителей на рынках, отличных от Tokopedia; когда потребители не «бегут» в Gojek, это означает, что они не находятся на одинаковом рынке. Чтобы предотвратить сбои в защите конфиденциальности при интеграции данных после слияния, компаниям необходимо оценить возможное совместное использование данных в рамках оценки рисков. Что касается прав субъекта данных, Компания должна уведомить субъект данных о слиянии и поглощении (M&A), учитывая право субъекта данных отказаться и гарантировать, что процесс M&A не нарушит права на конфиденциальность данных клиента.Ключевые слова: Закон о деловой конкуренции; цифровые платформы; слияние

Privacy Within the Private Order: A Critical Evaluation of the Market-Based System Governing Data Collection in the United States

This paper critically evaluates the market-based system governing data collection in the United States. The discussion is centred around Big Tech, a group of information intermediaries responsible for the ongoing extraction and exploitation of consumer data. The exploitative system is enabled by the ubiquitous privacy policy, which ostensibly offers data subjects ‘notice’ of data collection and the ‘choice’ to consent to said collection. This paper critiques the ‘notice and choice’ model, concluding the combined ambiguity and opacity of the privacy policy fail to offer subjects meaningful control over their data. To substantiate this argument, the paper evaluates the suitability of the market-based system in a broader sense, arguing that data collection practices precludes the knowledge parity necessary for an operative and fair market-based system. The paper concludes by ascertaining the suitability of state-based regulation, identifying data’s intrinsic relationship with ideals that are core to the Western tradition: equality, democracy, and autonomy.

Conversions on the rise – modernizing e-mail marketing practices by utilizing volunteered data

PurposeThe purpose of the study is to examine how utilizing volunteered data influences the response and unsubscribe rates of e-mail marketing to consumers.Design/methodology/approachIn three longitudinal field experiments conducted among 1,864 applicants of a higher education institution, the study compares customized marketing e-mails based on volunteered consumer data to e-mails that are personalized based on observed consumer data and to control e-mails that are not tailored by the marketer at all.FindingsThe results indicate that marketers should make consumers active participants in the communication process, as response rates are higher in those e-mails where volunteered data are utilized. However, the unsubscribe rate is the highest in customized e-mails.Research limitations/implicationsThe authors demonstrate that e-mails displaying empowering aspects influence consumers' behaviors and lead to outcomes that mostly outperform non-empowered e-mails.Practical implicationsCompared to other forms of interactive marketing, e-mail has lagged behind in both popularity and customer-friendly implementation. However, it has the potential to succeed if marketers pay more attention to consumer empowerment. As over 306 billion e-mails are sent worldwide daily and 75% of marketers use e-mail when contacting customers, the increase in response rates can have a significant influence on their returns.Originality/valueUnlike prior research the focus was on the process of tailoring, this perspective supports customer advocacy and emphasizes consumers' important role in creating engaging, empowering e-mail marketing communication.

Customer Analysis Using Machine Learning Algorithms: A Case Study Using Banking Consumer Dataset

The aim of each enterprise is to achieve high revenue from the business and to stay in a high position from their competitors. To archive high revenue and high position from competitors the need of understanding the business consumers is a crucial one. However the firm business is completely dependent on the consumers the efficient analysis of consumers within the enterprises makes to achieve the business to high position. To perform effective consumer analysis, in this study different machine learning is studied and experimented. ML classifiers make to understand in-depth analysis about the consumer data and further enables to plan wise decision strategies to enhance the business revenue and consumer satisfaction intelligently. The use of different ML classifiers is to sort out how the customer prediction outcome changes accordingly to the ML classifier is applied. This makes to find the best ML classifier for the consumer dataset applied in this study. The experimental procedure is performed using different ML classifiers and the outcome achieved is captured and projected using various validity scores. This work applies different ML classifiers like K-NN, C4.5, Random Forest, Random Tree, LR, MLP and NB for customer analysis. The empirical results illustrate the C4.5 model achieves better accuracy prediction compare to other ML classifiers and also compared with the time complexity NB model works efficiently with running time.

How consumers' personalities, lifestyles and demographics predict SVOD genre and SVOD platform consumption

PurposeStreaming video on demand (SVOD) services are comprised of digital media content creation and content distribution that provide a vast array of genre content playable on an assortment of different technology platforms. Additionally, these digital services are equipped to collect data and information on consumers. However, these services do not capture extensive consumer demographics, lifestyles or personalities information.Design/methodology/approachTo resolve this discrepancy, collecting external information such as complete demographics, personalities and lifestyles of consumers can be useful in advancing SVOD consumer behavior knowledge. This study examined how consumer demographics, lifestyles and personalities may predict SVOD genre consumption and SVOD platform consumption. A survey was executed and disseminated to collect consumer information across these dimensions. Multiple linear regressions and a structural equation model were formed to explicate variance.FindingsConsumer demographics, lifestyles and personalities’ information do predict SVOD genre consumption and SVOD platform consumption.Originality/valueMedia selection and trait theory have not been applied to understanding unexplained variance behind consumer media consumption, and are often used to predict media consumption variance among consumers. These findings illustrate that, while digital consumer touchpoints are necessary to collect and analyze, marketers should not lose sight of easily-obtainable consumer data, much of which dictates consumption choices.

The Welfare Impact of Targeted Advertising Technologies

We analyze the welfare implications of consumer data sharing, and restrictions to that sharing, in the context of online targeted advertising. Targeting technologies offer firms the ability to reach desired audiences through intermediary platforms. The platforms run auctions in real time to display ads on internet sites, leveraging consumers’ personal information collected online to personalize the ads. The online advertising industry posits that targeted advertising benefits advertising firms (that is, merchants who want to target ads to the desired consumers), consumers who see ads for preferred products, and the intermediary platforms that match consumers with firms. However, the claims that targeted advertising benefits all players involved have not been fully vetted in the literature. We develop an analytical model to analyze the economic and welfare implications of targeting technologies for those three players under alternative consumer information regimes. The regimes differ in the type and amount of consumer data available to the intermediary and to the advertising firms, and reflect the presence or absence of technological or regulatory restrictions to personal information flows. We find evidence of incentive misalignment among the players, as the intermediary prefers to share only a subset of consumer information with firms, whereas advertising firms prefer having complete information about the consumers. As such, a strategic intermediary with the ability to control which information is shared during the auction can have an incentive to use only the information that maximizes its payoff, overlooking the interests of both advertising firms and consumers. The information regimes that maximize consumer welfare vastly differ depending on consumers’ heterogeneity along two dimensions: a horizontal dimension, capturing consumer’s heterogeneity in product preferences; and a vertical dimension, capturing consumers’ heterogeneity in purchase power. Consumers prefer none of their personal information to be used for targeting only in limited circumstances. Otherwise, consumers are either indifferent or prefer only specific types of information to be used for targeting.

Local Energy Communities in Spain: Economic Implications of the New Tariff and Variable Coefficients

The European Union advocates for legislative support to local energy communities. Measures include the promotion of dynamic energy allocation and discriminatory electricity tariffs such as the recent Spanish framework. However, the impact of these normative changes is not yet evaluated. This paper inquires into the impact of dynamic allocation coefficient and different electricity tariffs on the profitability of local energy communities. To do so, a linear optimisation model is developed and applied to real consumer data in Spain around a variable capacity photovoltaic generation plant. Comparing the economic performance of the static or variable power allocation under the effect of changing electricity tariffs. While both measures are beneficial, the new electricity tariffs result in larger profitability increases than the planned variable coefficients. The combination of measures allows for profitability improvements of up to 25% being complementary measures. However, installations that maximise the potential for electricity generation are still not as profitable due to the low purchase price of surplus energy. While discriminatory electricity price tariffs and variable allocation coefficients are positive measures, further measures are needed for these communities to install generation plants as large as the potential that each case allows.