A resource-based view of intelligence dissemination and customer acceptance

Introduction

• Organizations have to be more and more innovative

• Knowledge management can be a positive influence on market orientation and thus innovative capacity

• Research question: How do SMEs use market knowledge as a resource in understanding their market’s needs in order to be more innovative?

• Market orientation

• Innovative capacity

• Knowledge management

Theoretical BackgroundMarket Orientation

• History of market orientation• Market orientation today

– Kohli & Jaworski (1990)– Narver & Slater (1990)– Day (1994)

• Intelligence generation, intelligence dissemination and responsiveness

Theoretical BackgroundInnovative capacity

• “Innovate or die”• Lot of research conducted in the topic:

Innovation, how does it work?• Types of innovation

– Innovativeness– Levels of innovation– Innovation for innovation’s sake

• Innovative capacity as a construct– Customer acceptance

Theoretical BackgroundKnowledge Management

• History of knowledge• Types of knowledge• Organizational knowledge

Theoretical BackgroundEntrepreneurship

• Research gap– Entrepreneurship in knowledge management, market

orientation and innovative capacity

• Firm size• Firm age

Theoretical BackgroundHypotheses

H1 - The better the intelligence dissemination of an organization, the better the customer acceptance of an organization.

Research MethodologyOverview

• Research Design• Research Sample• Research Measures

Research MethodologyResearch Design

• Quantitative research• (Web-based) Self-administrated survey• Drawbacks:

– Low response rate– May not be too long or complex

Research MethodologyResearch Sample

• Address Database ‘Groningen Province’ and ‘Groningen Municipality’

• Total of 18 addresses obtained• Discussion on the network site LinkedIn with the

request to fill in our web-based self-administrated survey

Research MethodologyResearch Measures

• Intelligence dissemination: MARKOR (Kohli & Jaworski, 1993), 8 statements on a five-point Likert scale

• Customer acceptance: Ledwith & O’Dwyer (2009), 4 statements on a five-point Likert scale

• Control variables: Firm size and firm age

ResultsOverview

• Survey• Descriptive statistics• Correlation• Regression analysis

ResultsSurvey

• Response rate on written survey: (2/18*100 =) 11,11 %

• Reasons:– Short time to respond

(TNT)– Quality of the questions

• Of the 12 returned surveys, 2 had to be deleted due to missing values

• Three other surveys (from LinkedIn) had to be deleted because the organizations weren’t entrepreneurships or innovative

ResultsDescriptive Statistics

N Mean Median St. Dev. Sum Min Max Cron alpha

Intelligence Dissemination 0,309 / 0,604

Hall talk 7 2,86 3,00 1,069 20 1 4

Interdepartmental meetings 7 2,29 2,00 0,951 16 1 4

Cross functions discussion 7 3,43 4,00 1,272 24 1 5

Document circulation 7 3,14 3,00 1,574 22 1 5

Important news share 7 4,14 4,00 0,690 29 3 5

Customer acc. dissemination 7 3,43 3,00 0,976 24 2 5

Com. marketing – manufacturing 7 4,14 5,00 1,215 29 2 5

Slow alert 7 3,71 4,00 1,496 26 1 5

Customer Acceptance 0,683

Customer acceptance 7 3,86 4,00 0,900 27 3 5

Customer satisfaction 7 3,71 4,00 0,756 26 3 5

Number of customers 7 3,29 3,00 0,951 23 2 5

Customer competitive advantage 7 3,57 3,00 0,787 25 3 5

Firm size 7 23,14 6,00 47,397 162 1 130

Firm age 7 4,86 5,00 3,388 34 1 10

ResultsDescriptive Statistics (2)

• Reliability analysis for constructs• Two items deleted in order to improve

Crombach’s alpha– Communication between Marketing and Manufacturing– Slow alert

ResultsCorrelations

Intelligence

Dissemination

Customer Satisfaction Firm Size Firm Age

Intelligence

Dissemination

-

Customer Satisfaction 0,720 * -

Firm Size 0,454 0,871 ** -

Firm Age 0,684 * 0,795 ** 0,678 * -

ResultsRegression

R2 = = 0,577 B St. Dev. Sig. (T)Constant 13,545 0,697 0.000 *Firm Size 0,040 0,014 0,025 *Firm Age -0,074 0,029 0,036 *

R2 = 0,899 B St. Dev. Sig. (T)

Constant 9,070 2,560 0,038 *

Intel. Dissemination 0,214 0,157 0,266

Firm Size 0,032 0,013 0,089 *

Firm Age 0,100 0,220 0,679

R2 = 0,518 B St. Dev. Sig. (T)

Constant 5,750 3,806 0,191

Intel. Dissemination 0,450 0,194 0,068 *

Multiple Linear Regression – Base Model

Multiple Linear Regression – Hypothesis 1

Single Linear Regression

ConclusionOverview

• Conclusion• Implications• Limitations

ConclusionConclusions

• Base model: All variables are significant• Hypothesis 1: Not supported by the multiple linear

regression, but supported by the single linear regression

• Research Question: How do SMEs use market knowledge as a resource in understanding their market’s needs in order to be more innovative?

• First part answered by the literature review in chapter 1.3

• Second part answered by the correlation and regression analysis

ConclusionConclusion (2)

• In summary:– By improving knowledge management system and

market knowledge acquiring, sharing between departments and among employees, will improve the market orientation described as intelligence dissemination, which in turns improves the innovative capacity, specifically customer acceptance

ConclusionImplications

• Improving an organization’s market orientation will improve the innovative capacity

• Knowledge Management is a good path to improve the market orientation of an organization

• The older an organization will be, the more effort must be spend on innovative capacity

ConclusionLimitations

• Simple size and response of the survey• The LinkedIn sample• Questions about departments• Only a small part of the conceptual model was

tested– Future Research should focus on

• The other relations in the conceptual model and on the • External validity of the model