Knowledge Integration and Organisational Performance of Data Analytics in the Family Business
Abstract
:1. Introduction
1.1. Knowledge-Based View Organisational Performance Theory
1.2. Knowledge Integration in the Family Business
1.3. Literature Review and Hypotheses Development
1.3.1. Relationship Conflict and Affective Commitment in the Family Business
1.3.2. Internal Social Capital and Affective Commitment in Family Businesses
1.3.3. The Role of Internal Social Capital as a Mediator between Relationship Conflict and Affective Commitment
1.3.4. Affective Commitment and Organisational Performance of Data Analytics
1.3.5. The Moderating Impact of Quality of Information
1.3.6. The Moderating Effect of Information Alignment
2. Materials and Methods
2.1. Data Collection and Sample
2.2. Variables and Measures
Constructs | Dimensions | Source | Items |
---|---|---|---|
Quality of information | Integrity | [76] | Contains complete information. They are presented without relevant gaps. They provide all the necessary information. |
Topicality | Provides the latest information. Provides up-to-date information. They always provide updated information. | ||
Format | They contain suitable formats. It is well designed. They are easy to understand. | ||
Precision | They provide correct information. They lack relevant errors. They provide accurate information. | ||
Internal social capital | [77] | They maintain open communication with each other. They do not keep company information to themselves. They are willing to share information with each other. They take advantage of their family relationships to share information. They show great integrity in their relationships. They trust each other. When making decisions, they consider the feelings of others. They are committed to the objectives of the company. They share the vision and mission of the company. They see themselves as partners in shaping the overall decision-making of the company. They share what the future of the company should be. | |
Affective commitment | [22] | They find their work challenging and exciting. They are clear about what is expected of them in the company. They feel heard by senior management regarding the ideas they present. They trust that the family business does what it promises to do. They have a feeling of fairness regarding the remuneration they receive They participate in the decision-making process considering the work and the operating rules of the company. | |
Relationship conflict | [33] | They have personal problems. They have obvious personality conflicts. They have tension in relationships. They are frequently in disagreement with the opinions of the CEO (Executive Director). They have frequent conflicts, about the different proposals presented in the company. They have conflicts regarding the work that each member of the family does in the company. They have differences of opinion about the company. | |
Organisational performance of data analytics | [16] | Data analytics improved customer retention Data analytics enhanced sales growth. Data analytics improved profitability. Data analytics allowed us to enter other markets faster than the competition. | |
Information alignment | [16] | The plan is aligned with the information quality objectives. The plan contains measurable goals that support data quality. The plan has initiatives that support the quality of information. The plan is aligned with the expected performance objectives of the business. The plan contains quantifiable goals that support the expected performance of the business. The plan has initiatives that support the expected performance of the business. We prioritize investments in data analysis by the expected impact on business performance. |
3. Results
3.1. Measurement Model
3.2. Structural Model
3.3. Interactive Analyses
3.3.1. Mediation
3.3.2. Moderation
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Company’s Age | n | % of Total | # of Employees | n | % Of Total |
---|---|---|---|---|---|
<10 | 4 | 3 | <10 10–50 51–250 >250 | 8 48 44 35 | 5.9 35.6 32.6 25.9 |
10–25 | 20 | 14.8 | |||
26–50 | 62 | 45.9 | |||
51–75 | 29 | 21.5 | |||
76–100 | 11 | 8.1 | |||
>100 | 9 | 6.7 | |||
TOTAL | 135 | 100 | TOTAL | 135 | 100 |
Industry | Internationalisation | ||||
Manufacturing | 80 | 59.3 | Yes | 35 | 25.9 |
Services | 55 | 40.7 | No | 100 | 74.1 |
TOTAL | 135 | 100 | TOTAL | 135 | 100 |
Variable | KMO | Cumulative Variance |
---|---|---|
Organisational performance of data analytics | 0.780 | 74.779% |
Affective commitment | 0.904 | 68.853% |
Internal social capital | 0.919 | 67.527% |
Relationship conflict | 0.870 | 71.383% |
Quality of information | 0.921 | 63.736% |
Information alignment | 0.821 | 69.801% |
Variable | Cronbach’s Alpha | Composite Reliability | Average Variance Extracted (AVE) |
---|---|---|---|
Organisational performance of data analytics | 0.880 | 0.926 | 0.806 |
Affective commitment | 0.872 | 0.921 | 0.796 |
Internal social capital | 0.870 | 0.920 | 0.793 |
Relationship conflict | 0.931 | 0.948 | 0.784 |
Quality of information | 0.940 | 0.949 | 0.676 |
Information alignment | 0.899 | 0.930 | 0.768 |
Variable | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
(1) Information alignment | 0.876 | |||||
(2) Quality of information | 0.681 | 0.822 | ||||
(3) Internal social capital | 0.306 | 0.209 | 0.891 | |||
(4) Affective commitment | 0.365 | 0.328 | 0.720 | 0.892 | ||
(5) Relationship conflict | −0.228 | −0.114 | −0.442 | −0.295 | 0.886 | |
(6) Organisational performance of data analytics | 0.452 | 0.458 | 0.149 | 0.303 | 0.112 | 0.898 |
Model | Hypothesis | Path | β | P |
---|---|---|---|---|
(1) | H4 | Organisational performance of data analytics ← Affective Commitment | 0.306 | 0.000 |
(2) | H4 | Organisational performance of data analytics ← Affective Commitment | 0.302 | 0.000 |
H2 | Affective Commitment ← Internal Social Capital | 0.720 | 0.000 | |
(3) | H4 | Organisational performance of data analytics ← Affective Commitment | 0.302 | 0.000 |
H2 | Affective Commitment ← Internal Social Capital | 0.729 | 0.000 | |
H1 | Affective Commitment ← Relationship Conflict | 0.020 | 0.397 | |
(4) | H4 | Organisational performance of data analytics ← Affective Commitment | 0.302 | 0.000 |
H2 | Affective Commitment ← Internal Social Capital | 0.733 | 0.000 | |
H1 | Affective Commitment ← Relationship Conflict | 0.029 | 0.365 | |
H3 | Internal Social Capital ← Relationship Conflict | −0.442 | 0.000 |
Path | (1) CSA | (2) Indirect Effect | (3) Indirect Effect |
---|---|---|---|
a: Internal Social Capital ← Relationship Conflict | −0.442 *** | −0.324 * | −0.325 * |
b: Affective Commitment ← Internal Social Capital | 0.732 *** | ||
c: Affective Commitment ← Relationship Conflict | −0.295 *** | ||
c‘: Affective Commitment ← Relationship Conflict | 0.029 |
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Barros-Contreras, I.; Morales-Serazzi, M.; Torres-Toukoumidis, A.; Palma-Ruiz, J.M. Knowledge Integration and Organisational Performance of Data Analytics in the Family Business. J. Open Innov. Technol. Mark. Complex. 2022, 8, 135. https://doi.org/10.3390/joitmc8030135
Barros-Contreras I, Morales-Serazzi M, Torres-Toukoumidis A, Palma-Ruiz JM. Knowledge Integration and Organisational Performance of Data Analytics in the Family Business. Journal of Open Innovation: Technology, Market, and Complexity. 2022; 8(3):135. https://doi.org/10.3390/joitmc8030135
Chicago/Turabian StyleBarros-Contreras, Ismael, Manuel Morales-Serazzi, Angel Torres-Toukoumidis, and Jesús Manuel Palma-Ruiz. 2022. "Knowledge Integration and Organisational Performance of Data Analytics in the Family Business" Journal of Open Innovation: Technology, Market, and Complexity 8, no. 3: 135. https://doi.org/10.3390/joitmc8030135