Change of Attitude, Technology and Practice: Identifying the Change for Increased Value Creation with Customer Co-creation

2017 ◽  
Vol 5 (1) ◽  
pp. 70-82
Author(s):  
Soumi Paul ◽  
Paola Peretti ◽  
Saroj Kumar Datta
Keyword(s):  
Social Media ◽  
New Product Development ◽  
Value Creation ◽  
Large Scale ◽  
Customer Orientation ◽  
Customer Relationships ◽  
Future Research ◽  
Management Competencies ◽  
Business Decisions ◽  
Prime Concern

Building customer relationships and customer equity is the prime concern in today’s business decisions. The emergence of internet, especially social media like Facebook and Twitter, changed traditional marketing thought to a great extent. The importance of customer orientation is reflected in the axiom, “The customer is the king”. A good number of organizations are engaging customers in their new product development activities via social media platforms. Co-creation, a new perspective in which customers are active co-creators of the products they buy and use, is currently challenging the traditional paradigm. The concept of co-creation involving the customer’s knowledge, creativity and judgment to generate value is considered not only an upcoming trend that introduces new products or services but also fitting their need and increasing value for money. Knowledge and innovation are inseparable. Knowledge management competencies and capacities are essential to any organization that aspires to be distinguished and innovative. The present work is an attempt to identify the change in value creation procedure along with one area of business, where co-creation can return significant dividends. It is on extending the brand or brand category through brand extension or line extension. This article, through an in depth literature review analysis, identifies the changes in every perspective of this paradigm shift and it presents a conceptual model of company-customer-brand-based co-creation activity via social media. The main objective is offering an agenda for future research of this emerging trend and ensuring the way to move from theory to practice. The paper acts as a proposal; it allows the organization to go for this change in a large scale and obtain early feedback on the idea presented. 

Value Creation in Business-to-Business Crowd Sourcing

Crowdsourcing ◽  
2019 ◽  
pp. 1419-1432
Author(s):  
Nina Helander ◽  
Hannu Kärkkäinen ◽  
Jari Jussila
Keyword(s):  
Social Media ◽  
Value Creation ◽  
Knowledge Society ◽  
Future Research ◽  
Full Potential ◽  
Crowd Sourcing ◽  
Multiple Case ◽  
Business To Consumer ◽  
Business To Business

In knowledge society the utilization of social media as a communication channel between people, groups and even companies is increasing. Current innovation and social media research has already shown the potential of crowdsourcing in the business-to-consumer (B2C) markets. The authors argue in this paper, however, that crowdsourcing has a great and yet partly undiscovered potential also in the context of business-to-business (B2B) markets. In order to get the full potential, a more detailed understanding of the logic of value creation in crowdsourcing activities between multiple stakeholders in B2B context is needed. This paper presents an exploratory study that is carried out as an empirical netnography-based multiple case study. The study opens up potential future research avenues by starting the discussion of value creation logic in B2B crowdsourcing. Practical implications are created through cases revealing what kind of value companies have already been able to gain from crowdsourcing in B2B context.

scholarly journals Human Sentiment and Activity Recognition in Disaster Situations Using Social Media Images Based on Deep Learning

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7115
Author(s):  
Amin Muhammad Sadiq ◽  
Huynsik Ahn ◽  
Young Bok Choi
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Large Scale ◽  
Activity Analysis ◽  
Physical Activities ◽  
Future Research ◽  
Crowd Sourcing ◽  
Emergency Relief ◽  
The Public ◽  
Text Streams

A rapidly increasing growth of social networks and the propensity of users to communicate their physical activities, thoughts, expressions, and viewpoints in text, visual, and audio material have opened up new possibilities and opportunities in sentiment and activity analysis. Although sentiment and activity analysis of text streams has been extensively studied in the literature, it is relatively recent yet challenging to evaluate sentiment and physical activities together from visuals such as photographs and videos. This paper emphasizes human sentiment in a socially crucial field, namely social media disaster/catastrophe analysis, with associated physical activity analysis. We suggest multi-tagging sentiment and associated activity analyzer fused with a a deep human count tracker, a pragmatic technique for multiple object tracking, and count in occluded circumstances with a reduced number of identity switches in disaster-related videos and images. A crowd-sourcing study has been conducted to analyze and annotate human activity and sentiments towards natural disasters and related images in social networks. The crowdsourcing study outcome into a large-scale benchmark dataset with three annotations sets each resolves distinct tasks. The presented analysis and dataset will anchor a baseline for future research in the domain. We believe that the proposed system will contribute to more viable communities by benefiting different stakeholders, such as news broadcasters, emergency relief organizations, and the public in general.

scholarly journals Impact of Training, Customer Orientation and Supervisory Behavior on Sales Performance

2020 ◽  
Vol 2 (2) ◽  
pp. 69-86
Author(s):  
Azeem Khan
Keyword(s):  
Social Media ◽  
Customer Orientation ◽  
Pearson Correlation ◽  
Sales Performance ◽  
Customer Relationship ◽  
Future Research ◽  
Global Village ◽  
Web Based ◽  
Diffusion Of Technology ◽  
Digital Era

This study examined the effect of Training, Customer Orientation and Supervisory Behavior on Salesforce Performance in the context of small and medium-sized companies (SMEs). The diffusion of technology, such as customer relationship management (CRM) systems and social media, has created a need to improve the understanding of how to manage interactions with customers in today’s digital era. The importance of technology is raised in terms of social media and as the world is treated as the “global village’. More importantly, the beginning of novelties such as cloud computing and web-based technology saves time and human efforts. The term, sales performance is the key to success for many organizations and is treated as the most demanding topic for firms. For this study, three hypotheses were formulated and tested with the help of Pearson correlation by using SPSS. Findings indicate that all the Training, Customer Orientation and supervisory behavioural dimensions were statistically significant and positively related to salesforce performance. Implications were drawn for future research and managerial attention.

A mobile visualization platform for exploring social media data

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yonghong Tong ◽  
Muhammet Bakan
Keyword(s):  
Social Media ◽  
Data Visualization ◽  
Mobile Device ◽  
Large Scale ◽  
Future Research ◽  
Social Media Data ◽  
Human Behaviors ◽  
Big Picture ◽  
Analysis Platform ◽  
Media Data

With the increasing application of using mobile device and social media, large amount of continuous information about human behaviors is available. Data visualization provides an insightful presentation for the large-scale social media datasets. The focus of this paper is on the development of a mobile-device based visualization and analysis platform for social media data for the purpose of retrieving and visualizing visitors’ information for a specific region. This developed platform allows users to view the “big picture” of the visitors’ locations information. The result shows that the developed platform 1) performs a satisfied data collection and data visualization on a mobile device, 2) assists users to understand the varieties of human behaviors while visiting a place, and 3) offers a feasible role in imaging immediate information from social media and leading to further policy-making in related sectors and areas. Future research opportunities and challenges for social media data visualization are discussed.Keywords: Social media, data visualization, mobile device

USING STARTUP COMMUNICATION FOR OPPORTUNITY RECOGNITION — AN APPROACH TO IDENTIFY FUTURE PRODUCT TRENDS

2016 ◽  
Vol 20 (08) ◽  
pp. 1640016 ◽  
Author(s):  
HAUKE SIMON ◽  
JENS LEKER
Keyword(s):  
Social Media ◽  
New Product Development ◽  
Large Scale ◽  
Early Stage ◽  
Hierarchical Cluster ◽  
Opportunity Recognition ◽  
Social Media Networks ◽  
New Information ◽  
Challenges And Opportunities ◽  
Traditional Approaches

A company’s ability to recognise early-stage opportunities and to understand the dynamics of emerging markets determines the success or failure of new products. Particularly the emergence of new information technology and social media networks provide ample opportunities to leverage a massive amount of data for managerial purposes. However, managers still meet using social media with skepticism and it is not fully understood how to make use of this information for new product development. We introduce a new method on how to use large-scale internet data as a complement to traditional approaches (patent or publication analysis and surveys) to overcome their shortcomings in terms of speed, dynamic and expense to conduct. More specifically, we propose that social media communication of startups can give valuable indications about future product trends especially in rapidly developing fields. Our approach measures the awareness of startups — and their products — as the increase of the communication about the startup on Twitter. Startup communication is a particularly well-suited indicator because startups develop new-to-the-world products or are in the development process. We illustrate our approach by analysing the communication of 545 startups. On a holistic level we determine industry trends. Fintech is among the topics that increase significantly in relevance. We determine more specific categories within the industries by applying cosine-similarity metrics and hierarchical cluster analysis. Subsequently we determine NPD relevant trends by the increase of retweets within these categories. The growing customer awareness of these clusters shows newly evolving customer needs. Incumbents may use this information to adjust to their current portfolio or to find collaboration partners to best meet upcoming challenges and opportunities. We think that the approach can be transferred to a multitude of fields, helping with the analysis of emerging fields and with early stage opportunity recognition.

Value Creation in Business-To-Business Crowd Sourcing

2014 ◽  
Vol 5 (1) ◽  
pp. 28-39 ◽  
Author(s):  
Nina Helander ◽  
Hannu Kärkkäinen ◽  
Jari Jussila
Keyword(s):  
Social Media ◽  
Value Creation ◽  
Knowledge Society ◽  
Future Research ◽  
Full Potential ◽  
Crowd Sourcing ◽  
Multiple Case ◽  
Business To Consumer ◽  
Business To Business

In knowledge society the utilization of social media as a communication channel between people, groups and even companies is increasing. Current innovation and social media research has already shown the potential of crowdsourcing in the business-to-consumer (B2C) markets. The authors argue in this paper, however, that crowdsourcing has a great and yet partly undiscovered potential also in the context of business-to-business (B2B) markets. In order to get the full potential, a more detailed understanding of the logic of value creation in crowdsourcing activities between multiple stakeholders in B2B context is needed. This paper presents an exploratory study that is carried out as an empirical netnography-based multiple case study. The study opens up potential future research avenues by starting the discussion of value creation logic in B2B crowdsourcing. Practical implications are created through cases revealing what kind of value companies have already been able to gain from crowdsourcing in B2B context.

Meeting Relationship-Marketing Goals Through Social Media: A Conceptual Model for Sport Marketers

2010 ◽  
Vol 3 (4) ◽  
pp. 422-437 ◽  
Author(s):  
Jo Williams ◽  
Susan J. Chinn
Keyword(s):  
Social Media ◽  
Relationship Marketing ◽  
Process Model ◽  
Customer Relationships ◽  
Relationship Building ◽  
Customer Relationship ◽  
Future Research ◽  
Sports Organizations ◽  
Building Process ◽  
Sport Industry

Sport industry marketers have long understood the importance of nurturing customer relationships. The new challenge is how best to face the shifts in customer relationship marketing posed by sports organizations and proactive consumers, or “prosumers.” In this article, the elements of the relationship-building process are presented with a focus on communication, interaction, and value, concepts identified in Gronroos’s (2004) relationship-marketing process model. An expanded version of Gronroos’s model is developed to include prosumers and to describe the interactions that occur through social-media exchanges. The value of specific social-media tools and Web 2.0 technologies in helping sport marketers meet their relationship-marketing goals is also discussed. Finally, directions for future research employing the expanded model are suggested.

scholarly journals Predicting the Quality of Short Narratives from Social Media

2017 ◽  
Author(s):  
Tong Wang ◽  
Ping Chen ◽  
Boyang Li
Keyword(s):  
Neural Networks ◽  
Social Media ◽  
Large Scale ◽  
Computational Models ◽  
Quality Evaluation ◽  
Future Research ◽  
Automatic Evaluation ◽  
Need To Evaluate ◽  
Difficult Challenge

An important and difficult challenge in building computational models for narratives is the automatic evaluation of narrative quality. Quality evaluation connects narrative understanding and generation as generation systems need to evaluate their own products. To circumvent difficulties in acquiring annotations, we employ upvotes in social media as an approximate measure for story quality. We collected 54,484 answers from a crowd-powered question-and-answer website, Quora, and then used active learning to build a classifier that labeled 28,320 answers as stories. To predict the number of upvotes without the use of social network features, we create neural networks that model textual regions and the interdependence among regions, which serve as strong benchmarks for future research. To our best knowledge, this is the first large-scale study for automatic evaluation of narrative quality.

Study and analysis of various sentiment classification strategies: A challenging overview

2021 ◽  
Author(s):  
Mandar Kundan Keakde ◽  
Akkalakshmi Muddana
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Performance Metrics ◽  
Research Area ◽  
Sentiment Classification ◽  
Future Research ◽  
Classification Schemes ◽  
Social Events ◽  
Election Prediction ◽  
Media Sentiment

In large-scale social media, sentiment classification is a significant one for connecting gaps among social media contents as well as real-world actions, including public emotional status monitoring, political election prediction, and so on. On the other hand, textual sentiment classification is well studied by various platforms, like Instagram, Twitter, etc. Sentiment classification has many advantages in various fields, like opinion polls, education, and e-commerce. Sentiment classification is an interesting and progressing research area due to its applications in several areas. The information is collected from various people about social, products, and social events by web in sentiment analysis. This review provides a detailed survey of 50 research papers presenting sentiment classification schemes such as active learning-based approach, aspect learning-based method, and machine learning-based approach. The analysis is presented based on the categorization of sentiment classification schemes, the dataset used, software tools utilized, published year, and the performance metrics. Finally, the issues of existing methods considering conventional sentiment classification strategies are elaborated to obtain improved contribution in devising significant sentiment classification strategies. Moreover, the probable future research directions in attaining efficient sentiment classification are provided.

Value Creation in Business-to-Business Crowd Sourcing

2019 ◽  
pp. 769-782
Author(s):  
Nina Helander ◽  
Hannu Kärkkäinen ◽  
Jari Jussila
Keyword(s):  
Social Media ◽  
Value Creation ◽  
Knowledge Society ◽  
Future Research ◽  
Full Potential ◽  
Crowd Sourcing ◽  
Multiple Case ◽  
Business To Consumer ◽  
Business To Business

In knowledge society the utilization of social media as a communication channel between people, groups and even companies is increasing. Current innovation and social media research has already shown the potential of crowdsourcing in the business-to-consumer (B2C) markets. The authors argue in this paper, however, that crowdsourcing has a great and yet partly undiscovered potential also in the context of business-to-business (B2B) markets. In order to get the full potential, a more detailed understanding of the logic of value creation in crowdsourcing activities between multiple stakeholders in B2B context is needed. This paper presents an exploratory study that is carried out as an empirical netnography-based multiple case study. The study opens up potential future research avenues by starting the discussion of value creation logic in B2B crowdsourcing. Practical implications are created through cases revealing what kind of value companies have already been able to gain from crowdsourcing in B2B context.

Sign in / Sign up

Export Citation Format

Share Document